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Member of Technical Staff, Applied AIThe opportunityWe are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.This is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.Who we areAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.Who you areYou are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.What sets you apart (preferred, not required)You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.Your responsibilitiesDevelop, deploy and adapt our models for customer environments:Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.Ensure deployments meet customer standards for security, performance and reliability.Customer partnership & product feedback:Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.Create technical documentation, integration guides and best-practice resources.Spend time working on-site at international partner locations as needed.Self development:Stay on top of the latest developments in ML, model serving and cloud-native tooling.Gain a strong working understanding of protein and cell biology.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Participate in knowledge sharing, e.g. organise and present at our internal reading group.Attend and present at conferences.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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Member of Technical Staff, Applied AIThe opportunityWe are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.This is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.Who we areAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.Who you areYou are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.What sets you apart (preferred, not required)You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.Your responsibilitiesDevelop, deploy and adapt our models for customer environments:Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.Ensure deployments meet customer standards for security, performance and reliability.Customer partnership & product feedback:Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.Create technical documentation, integration guides and best-practice resources.Spend time working on-site at international partner locations as needed.Self development:Stay on top of the latest developments in ML, model serving and cloud-native tooling.Gain a strong working understanding of protein and cell biology.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Participate in knowledge sharing, e.g. organise and present at our internal reading group.Attend and present at conferences.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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About GigaGiga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:Voice AI startup Giga raises $61M Series ADoorDash and Giga PartnershipGiga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!The RoleWe're looking for new grad engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers.This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.What You'll Work OnYou'll contribute to projects across our stack. Some examples:Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resourcesActivity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behaviorDynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pagesAgent memory: Conversation awareness and recent interaction lookups so agents remember context across sessionsYou'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.You Might Be a Fit If YouAre graduating (or recently graduated) with a CS degree or equivalent backgroundHave internship experience or significant projects where you wrote production-quality codeCan take a problem, figure out an approach, and unblock yourself when you get stuckPrefer shipping over perfection but still care about qualityWant to work at a startup where you'll have real responsibility earlyPerks & BenefitsCatered lunch dailyDinner stipend$150/month wellness benefit (gym, fitness classes, mental health)401(k) planCommuter benefitsMedical, dental, and vision coverageGiga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

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About GigaGiga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:Voice AI startup Giga raises $61M Series ADoorDash and Giga PartnershipGiga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!The RoleWe're looking for backend engineers to build the infrastructure and systems that power our AI agents. You'll work across the stack, from data pipelines and analytics to real-time agent systems, shipping features that directly impact how our customers operate.This isn't a role where you'll be handed a spec and asked to execute. You'll own problems end-to-end: figuring out the right approach, building it, and iterating based on what you learn.What You'll Work OnA few examples from our current roadmap:Analytics rewrite: Migrating our analytics service to ClickHouse and rebuilding it to scale through our next 10x of growthHallucination detection: Improving our detection systems with the goal of driving hallucination rates toward zeroBrowser use agent: Scaling, stabilizing, and adding features and accuracy to our browser use agent in lieu of formal customer APIsAs a senior engineer, you'll be expected to make sound technical decisions, ship reliably, and help set the bar for code quality and system design. You'll have significant autonomy and influence over what gets built and how.Tech StackBackend: Python (Django/FastAPI), TypeScript (Node.js)Infrastructure: AWS, Modal, Kubernetes, PostgresFrontend: TypeScript, Next.js (you'll interact with this, but it's not the focus)You Might Be a Fit If YouHave 4+ years building backend systems, ideally at companies where reliability and scale matteredAre comfortable with ambiguity: you can take a loosely-defined problem and figure out what to buildYou'll jump into unfamiliar parts of the codebase when that's what the problem requiresWrite clean code and care about getting the details right, but also know when to shipWant to work on hard problems with a small team where your work has obvious impactAre excited about AI agents and the infrastructure challenges that come with running them in productionPerks & BenefitsCatered lunch dailyDinner stipend$150/month wellness benefit (gym, fitness classes, mental health)401(k) planCommuter benefitsMedical, dental, and vision coverageGiga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

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About GigaGiga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:Voice AI startup Giga raises $61M Series ADoorDash and Giga PartnershipGiga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!The RoleWe're looking for software engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers who will help you grow.This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.What You'll Work OnYou'll contribute to projects across our stack. Some examples:Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resourcesActivity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behaviorDynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pagesAgent memory: Conversation awareness and recent interaction lookups so agents remember context across sessionsAs an early-career engineer, you'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.You Might Be a Fit If YouHave 1-3 years of professional software engineering experienceAre curious and ask good questions—you want to understand why things work, not just howCan take feedback well and iterate quicklyPrefer shipping over perfection but still care about qualityWant to grow at a startup where you'll have real responsibility earlyPerks & BenefitsCatered lunch dailyDinner stipend$150/month wellness benefit (gym, fitness classes, mental health)401(k) planPaid parental leave (12 weeks maternal, 6 weeks paternal)Commuter benefitsMedical, dental, and vision coverageGiga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is accelerating the future of AI and high-performance compute by building industry-leading CPU and AI architectures. As an Automotive and Robotics SoC Architect, you will define scalable, top-down system architectures that unify our CPU and AI technologies for next-generation automotive applications. This senior technical role shapes the architectural direction of our automotive and robotics portfolio, ensuring our products meet the industry's highest expectations for performance, safety, reliability, and security. This position is central to how Tenstorrent delivers world-class automotive solutions and requires strong technical leadership, systems thinking, and cross-functional collaboration. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are A systems thinker who can architect complex SoCs from concept to execution. A strong communicator who can articulate technical direction across engineering teams and external partners. Someone with deep knowledge of safety-critical systems and the unique needs of automotive environments. An innovator who can identify future use cases and propose next-generation architectural solutions. A leader who thrives in a highly technical, cross-functional, fast-moving environment.   What We Need Bachelor’s, Master’s, or Ph.D. in Electrical Engineering, Computer Engineering, or related field. Extensive experience designing complex SoCs, ideally in automotive applications. Proficiency in hardware description languages such as Verilog or VHDL. Experience with hardware/software co-design and co-verification. Knowledge of automotive safety standards (e.g., ISO 26262) and security principles. Someone comfortable with up to 25% international travel.  Experience with both cameras, sensors, and others is a plus.   What You Will Learn How cutting-edge CPU and AI architectures are adapted for automotive-grade environments. Best-in-class methodologies for safety-critical SoC design, verification, and system integration. How to translate emerging automotive use cases into scalable, future-proof SoC architectures. Approaches to hardware-level security, robustness, and cyber-resilience in automotive compute systems. Cross-functional collaboration strategies that drive innovation across architecture, software, DV, and product teams.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Hi, we're The Browser Company 👋 and we're building a better way to use the internet. Browsers are unique in that they are one of the only pieces of software that you share with your parents as well as your kids. Which makes sense, they're our doorway to the most important things — through them we socialize with loved ones, work on our passion projects, and explore our curiosities. But on their own, they don’t actually do a whole lot, they’re kind of just there. They don’t help us organize our messy lives or make it easier to compose our ideas. We believe that the browser could do so much more — it can empower and support the amazing things we do on the internet. That’s why we’re building one: a browser that can help us grow, create, and stay curious. To accomplish this lofty task, we’re building a diverse team of people from different backgrounds and experiences. This isn’t optional, it’s crucial to our mission, as we need a wide range of perspectives to challenge our assumptions and shape our browser through a bold, creative lens. With that in mind, we especially encourage women, people of color, and others from historically marginalized groups to apply.About the RoleBuilding software is changing. With modern AI coding tools and automated reviewers, the bottlenecks in shipping products are shifting from “how fast can you type” to “how have you designed the system that writes, reviews, and ships the code.” At The Browser Company, we believe this shift is so profound that how we build is as important, and ultimately as defensible, as what we build.We’re investing deeply in “building how we build”: an AI‑native development stack that turns our way of working into compounding leverage for every engineer and team. Our vision is a world where most code is generated and reviewed by AI, where model training and prompt optimization are automated, and where product builders operate at a higher layer—seeing trends, deciding what to build, and clicking the “right” buttons rather than hand‑crafting every line.As our Technical Lead for Developer Experience at Browser Company, you won’t just maintain tools or CI pipelines–you’ll lead the creation of a second product: an internal, AI‑powered software generation and review platform that changes how Dia gets built.Overall you will...Design and lead the “build how we build” platform: an internal SaaS‑like experience where engineers and non‑engineers can describe what they want, and our system realizes the rest.Partner with AI and infra teams to wire together the pieces we already have—AI coding tools, virtualized environments, CI, AI code reviewers, evals, and prompt and model optimization—into a cohesive, opinionated product that our teams love to use.Define success metrics for this platform and iterate quickly based on real usage and feedback from our engineers.Turn our DevEx stack into true leverage, so that every engineer and PM can move with 10x more impact.Qualifications5+ years of experience with developer tools and build environments, open-source developer tooling, or low-level systems experience.Experience owning a zero‑to‑one product or platform, ideally in a role with founder‑like autonomy (founder/CTO, tech lead, staff/principal on a platform or DevEx team).You're passionate about building tools and systems that make other engineers more productive and strive to make them elegant and maintainable.You thrive in a high‑trust, high‑ambiguity environment: you seek feedback, but you don’t need hand‑holding.We’re primarily focused on hiring in North American time zones and require that folks have 4+ hours of overlap time with team members in Eastern Time Zone.Compensation and BenefitsOur total compensation package for full-time employees includes base salary, equity, and benefits. The annual salary range for this role is $290,000 - $340,000 USD. The actual salary offered will vary based on experience level and interview performance.Benefits: We offer a wide range of perks and benefits designed to support you, your family, and help you engage with your local community. To learn more, visit go.atlassian.com/perksandbenefits.Location: We’re a remote-friendly company and can hire in any country where Atlassian has a legal entity. If you live in New York (or want to visit), you’re welcome to work from our beautiful office in Williamsburg.The Browser Company is an ambitious team of close to 100 people (and growing!) who are passionate about building great products. We are a remote-first, distributed team, with the option to work from office in Brooklyn, New York. We strongly support diversity and encourage people from all backgrounds to apply.  🚙 To read more about what we value as a company, check out Notes on Roadtrips on our blog.

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Ryz Labs is looking for a Full Stack AI Engineer – Prod Support to build intelligent, secure, and scalable identity experiences across our client's platforms. In this role, you’ll work end-to-end—from frontend UX to backend services and AI models—focusing on authentication, authorization, identity verification, fraud detection, and personalization.You’ll partner closely with product, security, and data teams to embed AI into identity workflows whilemaintaining the highest standards of privacy, security, and reliability. Responsibilities:- Design, build, and deploy AI/ML solutions to automate ITSM ticket triage, classification, prioritization, androuting- Develop NLP-based models for ticket summarization, root-cause detection, and resolutionrecommendation- Implement AI-powered virtual agents / copilots to assist support engineers and end users- Partner with Product Support, SRE, and Engineering teams to understand recurring issues and automateresolution workflows- Build intelligent runbooks and self-healing automation for common incidents and service requests- Enhance knowledge management by auto-generating and updating KB articles from resolved tickets- Integrate AI solutions with ITSM platforms (HALO)- Develop APIs, workflows, and event-driven automations across monitoring, logging, and ITSM tools- Ensure seamless handoff between AI systems and human support engineers- Analyze ticket, incident, and operational data to identify automation opportunities- Train, evaluate, and continuously improve ML models using real-world support data- Implement monitoring for model performance, drift, and accuracy in production- Ensure AI solutions meet reliability, security, and compliance standards- Implement guardrails, explainability, and auditability for AI-driven decisions- Contribute to AI governance and responsible AI practices Qualifications/Requirements of the Position: - 5+ years of experience as a Full Stack Engineer, Platform Engineer, or AI Engineer, with ownership ofproduction systems- Strong proficiency in JavaScript/TypeScript and a modern frontend framework (React, Next.js, orequivalent)- Backend development experience with Python, Java, or Node.js, including building and maintaining secureAPIs- Hands-on experience delivering AI/ML solutions into production environments- Strong experience in Python and/or Java for backend and ML development- Hands-on experience with NLP, LLMs, or GenAI (e.g., transformers, embeddings, RAG, promptengineering)- Experience integrating AI solutions with ITSM tools (HALO, etc.)- Knowledge of REST APIs, microservices, and cloud platforms (AWS, Azure, or GCP)- Familiarity with MLOps, CI/CD, model deployment, and monitoring- Solid understanding of ITIL / ITSM processes (Incident, Problem, Change, Request)- Experience working with Product Support, SRE, or NOC teams- Ability to translate operational pain points into automation and AI use cases Knowledge, Skills, and Abilities Required: - Background in cybersecurity, fraud detection, trust & safety, or abuse prevention. - Experience with graph-based ML, NLP for security signals, or time-series anomaly detection.- Knowledge of adversarial ML, model evasion techniques, or secure model design.- Experience building systems that operate under strict latency or reliability constraints.- Exposure to chatbots, copilots, or agentic AI frameworks- Experience in high-volume, 24x7 production support environments- Publications, talks, or open-source contributions in AI or security. About RYZ Labs:RYZ Labs is a startup studio founded in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together was their passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge cloud computing technologies to create scalable and resilient applications. We aim to provide diverse product solutions for different industries and plan to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:- Customer First Mentality - Every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership - Step up if you see an opportunity to help, even if it's not your core responsibility. - Humility and Respect - Be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less- Deliver Impact - get things done most efficiently. - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.

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Remote position, only for professionals based in Argentina or Uruguay At Ryz Labs we are looking for a Full Stack AI Engineer – BuilderEx to build intelligent, secure, and scalable identity experiences across our platforms. In this role, you will work end-to-end—from frontend UX to backend services and AI models—focusing on authentication, authorization, identity verification, fraud detection, and personalization.This role combines full stack engineering, AI/ML integration, and identity architecture, with close collaboration across product, security, and platform teams to deliver privacy-first, highly reliable systems. Essential Responsibilities:Design, build, and maintain full-stack applications powering identity and access management (IAM) experiences.Develop and integrate AI/ML models for identity use cases such as fraud detection, anomaly detection, risk-based authentication, and identity verification.Lead and execute SSO migrations across products and platforms, consolidating authentication flows while minimizing user disruption.Drive domain consolidation initiatives by unifying identity systems, services, and user data models across multiple platforms or brands.Improve developer experience (DevEx) by building internal tools, SDKs, APIs, and documentation that simplify identity integrations.Design and evolve secure, scalable APIs supporting authentication, authorization, and identity data services.Partner closely with Security, Platform, and Product teams to implement and standardize protocols and patterns such as OAuth 2.0, OpenID Connect, SAML, JWT, and zero-trust architectures.Ensure AI-powered identity systems are observable, explainable, and production-ready, with robust monitoring and feedback loops.Balance security, performance, and usability while maintaining high standards for privacy and compliance.Contribute to architectural decisions, technical design discussions, and code quality standards. Qualifications / Requirements of the Position:5+ years of experience as a Full Stack Engineer, Platform Engineer, or AI Engineer with ownership of production systems.Strong proficiency in JavaScript/TypeScript and modern frontend frameworks (React, Next.js, or equivalent).Backend development experience with Python, Java, or Node.js, including building secure, scalable APIs.Hands-on experience delivering AI/ML solutions into production environments.Solid understanding of identity and access management (IAM) concepts, including authentication, authorization, and identity lifecycle.Proven experience leading or contributing to SSO migrations using OAuth 2.0, OpenID Connect, and/or SAML.Experience with domain consolidation or identity unification initiatives across multiple applications or platforms.Demonstrated ability to improve developer experience (DevEx) through internal tooling, APIs, SDKs, or platform improvements.Experience working with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes).Strong security mindset, including experience designing systems with privacy, compliance, and resilience in mind.Ability to collaborate cross-functionally and communicate complex technical concepts clearly. Knowledge, Skills, and Abilities Required:Background in cybersecurity, fraud detection, trust & safety, or abuse prevention.Experience with graph-based ML, NLP for security signals, or time-series anomaly detection.Knowledge of adversarial ML, model evasion techniques, or secure model design.Experience building systems operating under strict latency or reliability constraints.Prior work in regulated or high-risk environments.Security certifications or relevant coursework (e.g., OSCP, CISSP concepts).Experience with SIEM/SOAR tools or security telemetry platforms.Publications, talks, or open-source contributions in AI, security, or related fields.

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Eight Sleep is the world’s first sleep fitness company. Our mission is to fuel human potential through optimal sleep. We use innovative technology, detailed design, and proven science and data to personalize and improve each night for everybody—changing the way people sleep forever and for the better.Backed by leading Silicon Valley investors, we have been recognized as one of Fast Company’s Most Innovative Companies in 2018, 2022, and 2023.Our temperature-regulated technology, the Pod, is an absolute game changer, improving people's health and happiness by changing the way they sleep. The Pod was also recognized two years in a row by TIME's “Best Inventions of the Year.” It is available for purchase in North America (the United States and Canada) and throughout the United Kingdom, Europe (Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, Denmark), and Australia via eightsleep.com. We’re excited by the success of the Pod to date and still have a long way to go toward achieving our mission.Join our team as a Sr MLOps Engineer to help us bring current and next generations of Pod ML models to life. You'll be a part of a small team designing and implementing solutions with high levels of autonomy to bring our members better sleep. Your work will go directly to our fleet of existing Pods with low friction and direct impact to the business. We are a fast moving and fast growing company, and we embrace individuals with a growth mindset and strong desire to help us achieve our mission: Improving people's lives through optimal sleep.How you’ll contributePioneer Cutting-Edge Technology: Introduce and implement cutting-edge ML technologies, integrating them into our products and processes to enable the future of health monitoringEnd-to-End Ownership: Own design and operation of robust ML infrastructure – building scalable data, model, and deployment pipelines that ensure reliable delivery of models to production.Cross-functional Collaboration Partner with R&D, firmware, data, and backend teams to ensure ML inference operates reliably and scales to Pods everywhere.Optimize for Performance: Drive cost-effective, scalable, and high-performance ML systems by optimizing compute, storage, and deployment resources across training and inferenceEnhance Tooling and Platforms: Develop tooling, micro services, and frameworks to streamline data processing, experimentation, and deploymentEffective Remote Communication: Thrive in a remote work environment, ensuring clear and direct communication.What you need to succeedProven Expertise: 5+ years of software engineering experience with a focus on ML infrastructure, distributed systems, or large-scale data processing in Python (e.g., PyTorch, TensorFlow, or similar).ML Operations Mastery: Hands-on experience with ML workflow orchestration and CI/CD pipelines for model deployment.Scalable Deployment Experience: Demonstrated success shipping ML models to production at scale, handling telemetry, monitoring, and feedback loops across large device fleets or user populations.Cloud-Native Expertise: Strong experience with AWS (Lambda, ECS, DynamoDB, CloudWatch) or equivalent cloud platforms for serving and monitoring ML systems.Adaptive Problem Solver: A fast-paced, collaborative, and iterative approach to tackling complex problems.What sets you apart:Expertise in real-time ML workflows and streaming systems (e.g., Kinesis, Kafka, Flink).Demonstrated expertise in optimizing ML infrastructure for efficiency, latency, and cloud cost at scale.Understanding of secure ML operations, privacy practices, and compliance considerations, particularly for health-related or IoT data.Familiarity with health, wellness, or IoT domains, especially wearables or medical-grade devices.Why join Eight Sleep?Innovation in a culture of excellenceJoin us in a workplace where innovation isn’t just encouraged - it’s a standard. Our flagship product, the Pod, is a testament to our culture of excellence, beloved by hundreds of thousands of customers worldwide. At Eight Sleep, you will be part of a team that continuously pushes the boundaries of technology in sleep fitness.Immediate responsibility and accelerated career growthFrom your first day, you’ll take on substantial responsibilities that have a direct impact on our core business and product success. We are a small team that empowers you to own your projects and see the tangible effects of your efforts, enhancing both your professional growth and our company’s trajectory. Your path will be challenging but rewarding, perfect for those who thrive in fast-paced environments aiming for high standards.Collaboration with exceptional talentWork alongside other bright minds like you: at Eight Sleep exceptional intelligence and a passion for breakthroughs are the norms. Our team members are not only experts in their fields but also avid innovators who thrive in our dynamic, fast-paced environment.Equitable compensation and continuous equity investmentWe extend equity participation to every full-time team member, recognizing and rewarding your direct contributions to our success. This includes periodic equity refreshments based on performance, ensuring that as Eight Sleep grows and succeeds, so do you – perfectly aligning your achievements with the broader triumphs of the company.Your own Pod - and other great benefitsEvery Eight Sleep employee receives the very product that defines our mission: a Pod of their own. If you join us you’ll get your own Pod, along with*:Full access to health, vision, and dental insurance for you and your dependentsSupplemental life insuranceFlexible PTOCommuter benefits to ease your daily commutePaid parental leave*List of benefits may vary depending on your locationAt Eight Sleep we continually celebrate the diverse community different individuals cultivate. As an equal opportunity employer, we stay true to our values by ensuring everyone feels they can flourish and grow. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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About LangfuseOpen Source LLM Engineering Platform that helps teams build useful AI applications via tracing, evaluation, and prompt management (mission, product). We are now part of ClickHouse.We're building the "Datadog" of this category; model capabilities continue to improve, but building useful applications is really hard, both in startups and enterprises.Largest open source solution in this category: trusted by 19 of the Fortune 50, >2k customers, >26M monthly SDK downloads, >6M Docker pulls.We joined ClickHouse in January 2026 because LLM observability is fundamentally a data problem and Langfuse already ran on ClickHouse. Together we can move faster on product while staying true to open source and self-hosting, and join forces on GTM and sales to accelerate revenue.Previously backed by Y Combinator, Lightspeed, and General Catalyst.We're a small, engineering-heavy, and experienced team in Berlin and San Francisco. We are also hiring for engineering in EU timezones and expect one week per month in our Berlin office (how we work).Your impactMake our best customers successful in production and expanding over time.Improve net revenue retention via adoption, outcomes, and proactive risk management.Scale your impact to our large user base and OSS community by contributing to documentation, guides, and other public content.Create a tight loop from “what customers do” (your deep understanding of top customers) → “what we should build” (feedback to the product engineering team) → “how the GTM org explains it.” (GTM enablement).What you’ll do1) Own strategic customer relationships (portfolio ownership)Be the primary technical partner for 10–20 strategic accounts (large, highly engaged, or aligned with our roadmap).Run onboarding, success planning, and regular deep dives into the customer’s AI architecture and workflows.Drive adoption of key product capabilities across the lifecycle: initial setup, team workflows, scaling, and expansion.2) Production readiness + architectural guidanceLead customers through production readiness: instrumentation strategy, data modeling choices, evaluation setup, alerting/monitoring expectations, security & privacy considerations, and operational playbooks.Provide pragmatic architecture guidance for real LLM systems (agents, tool use, RAG, evals, prompt iteration, dataset curation, feedback loops).Build small prototypes, reference implementations, and demos when it unblocks a customer. Turn them into reusable templates that can be published.3) Escalation leadershipOwn the technical leadership during high-severity customer moments: triage, root-cause coordination, and crisp communication.Be the point of contact for the customer and partner closely with Engineering, be proactive in how you resolve issues.Establish escalation paths, runbooks, and prevention mechanisms for repeat issues.4) Turn customer signal into product + docs + enablementAggregate patterns across your portfolio and translate them into actionable product feedback (clear problem statements, impact, and recommended solutions).Create customer-facing assets (docs, guides, best practices, demos) that start as one customer’s question and become durable collateral.Enable the broader ClickHouse GTM org: training, playbooks, crisp messaging, and “how to win” narratives for AI engineering teams.What we’re looking forMust-havesSenior experience in a customer-facing technical role: TAM, Solutions Engineer, Solutions Architect, Forward Deployed Engineer, Customer Success Engineer, or similar where you owned outcomes.Strong technical foundation: you can debug integrations, reason about distributed systems, APIs/SDKs, and cloud infrastructure.Demonstrated work in applied AI / AI engineering: building, operating, or enabling LLM applications (agents, RAG, eval pipelines, prompt tooling, experimentation).Excellent communication: you can lead technical meetings, drive decisions, and write docs engineers actually follow.High ownership: you ship artifacts, close loops, and create repeatable systems rather than bespoke one-offs.Nice-to-havesExperience with devtools / OSS ecosystems and developer-centric GTM.Familiarity with observability concepts (tracing/metrics/logs), data pipelines, and evaluation frameworks.Track record of technical writing or enablement (workshops, reference architectures, public docs).ProcessWe can run the full process to your offer letter in less than 7 days (hiring process).Tech StackWe run a TypeScript monorepo: Next.js on the frontend, Express workers for background jobs, PostgreSQL for transactional data, ClickHouse for tracing at scale, S3 for file storage, and Redis for queues and caching. You should be familiar with a good chunk of this, but we trust you'll pick up the rest quickly (Stack, Architecture).How we shipLink to handbookWe trust you to take ownership (ownership overview) for your area. You identify what to build, propose solutions (RFCs), and ship them. Everyone here thinks about the user experience and the technical implementation at the same time. Everyone manages their own Linear.You're never alone. Anyone from the team is happy to go into a whiteboard session with you. 15 minutes of shared discussion can very much improve the overall output.We implement maker schedule and communication. There are two recurring meetings a week: Monday check-in on priorities (15 min) and a demo session on Fridays (60 min).Code reviews are mentorship. New joiners get all PRs reviewed to learn the codebase, patterns, and how the systems work (onboarding guide).We use AI as much as possible in our workflows to make our users happy. We encourage everyone to experiment with new tooling and AI workflows.Why Langfuse (now part of ClickHouse)This role puts you at the forefront of the AI revolution, partnering with engineering teams who are building the technology that will define the next decade(s).This is an open-source devtools company. We ship daily, talk to customers constantly, and fight for great DX. Reliability and performance are central requirements.Your work ships under your name. You'll appear on changelog posts for the features you build, and during launch weeks, you'll produce videos to announce what you've shipped to the community. You’ll own the full delivery end to end.We're solving hard engineering problems: figuring out which features actually help users improve AI product performance, building SDKs developers love, visualizing data-rich traces, rendering massive LLM prompts and completions efficiently in the UI, and processing terabytes of data per day through our ingestion pipeline.You'll work closely with the ClickHouse team and learn how they build a world-class infrastructure company. We're in a period of strong growth: Langfuse is growing organically and accelerating through ClickHouse's GTM. (Why we joined ClickHouse)If you wonder what to build next, our users are a Slack message or a Github discussions post away.You’re on a continuous learning journey. The AI space develops at breakneck speed and our customers are at the forefront. We need to be ready to meet them where they are and deliver the tools they need just-in-time.

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About the team​​The Safety Systems org ensures that OpenAI’s most capable models can be responsibly developed and deployed. We build evaluations, safeguards, and safety frameworks that help our models behave as intended in real-world settings.The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework.Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.The mission of the Preparedness team is to:Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards risks whose impact could be catastrophicEnsure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systemsPreparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.About the roleModels are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve.In this role, you will:Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership.Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities.Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model utility, and user privacy) and propose pragmatic, testable solutions.Collaborate closely with risk and threat modeling partners to align mitigation design with anticipated attacker behaviors and high-impact misuse scenarios.Execute rigorous testing and red-teaming workflows, helping stress-test the mitigation stack against evolving threats (e.g., novel exploits, tool-use chains, automated attack workflows) and across different product surfaces—then iterate based on findings.You might thrive in this role if you:Have a passion for AI safety and are motivated to make cutting-edge AI models safer for real-world use.Bring demonstrated experience in deep learning and transformer models.Are proficient with frameworks such as PyTorch or TensorFlow.Possess a strong foundation in data structures, algorithms, and software engineering principles.Are familiar with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization.Excel at working collaboratively with cross-functional teams across research, security, policy, product, and engineering.Have significant experience designing and deploying technical safeguards for abuse prevention, detection, and enforcement at scale.(Nice to have) Bring background knowledge in cybersecurity or adjacent fields.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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We are seeking a Computational Protein Design Scientist to join our team working at the interface of generative AI and synthetic biology. You will play a key role amongst a team of scientists designing and engineering proteins for specific functions. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. Using your blend of computational expertise and in-depth biochemical understanding of proteins, you will generate insights to improve protein functionality and operate at the interface between our machine learning and experimental platform units, working closely to seamlessly integrate AI generations and lab validation data.Who you areYou are a computational protein designer. You have a proven track record of successfully leveraging novel computational tools and knowledge of biochemistry or structural biology to design proteins to functional requirements and applications in synthetic biology.You are a data scientist. You are a strong data scientist and you have experience owning data-driven projects to generate biological insights.You are a successful scientist. You have a PhD (or equivalent industry experience) in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bio/chem engineering, or a related field. Your research experience was in protein biochemistry using computational expertise.You collaborate with experimentalists. You have experience collaborating with experimental (i.e. wet lab) teams to achieve protein design objectives.You are an owner. You have a proven track record of delivering successful commercial and / or academic research projects, demonstrated through publications, patents, and/or commercially impactful outcomes, as well as other contributions to the scientific community.You are a connector. You love to connect people and enable them to perform at their highest levels. You have excellent communication and presentation skills with the ability to convey complex scientific concepts to both technical and non-technical audiences.You are a mission driven innovator. You are passionate about making a positive impact on the world, whether it's for patients, partners or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies.You thrive in a dynamic and ambiguous environment. You excel in a fast-paced setting where goals must be achieved efficiently and urgently. You have a keen eye for creating, then optimizing processes to improve speed and repeatability. You are an advocate for lab automation, both through hardware and softwareWhat sets you apart (preferred but not required)You have experience with generative AI. You have experience leveraging generative AI (or other machine learning models) in synthetic biology applications.You have experience engineering gene editing tools, such as nucleases and integrases.You have experience with homology-based and structural bioinformatics, and are able to answer scientific questions using very large databases.You have helped scale a young biotech before. You have worked in startups and helped the company grow.Your ResponsibilitiesLeverage our proprietary generative AI models to design proteins for experimental validation:Analyze protein design problems based on functional requirements, biochemistry, structural biology and sequence homologyGenerate designs using our proprietary generative AI models and optimize designs for experimental validationCoordinate with our lab-based protein engineers to plan and optimize the design process and validation strategyLeverage our proprietary data to improve our models:Analyze and leverage our experimental results to improve the next round of designs and increase our success rate over validation roundsCollaborate with machine learning scientists to fine-tune and prompt our modelsCollaboration and communication:Be an effective interface between machine learning model development and experimental validationCapture bioengineering learnings and feedback to our machine learning unit, and vice versaFoster a collaborative and innovative environment, proactively finding opportunities to innovate and create clarity and alignment between different unitsContribute to our computational tools:Help improve the way we use, serve and integrate our AI models, by feeding back to the software engineers and foundational machine learning unitHelp improve our data management systems and workflowsScientific excellence and self development:Work to the highest scientific standards (publication-grade work) Stay on top of relevant developments in synthetic biologyContinue building your understanding of generative AI as well as expanded areas of protein and cell biologyParticipate in knowledge sharing, e.g. organize and present at our internal reading group.Attend and present at conferences when relevant.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension/401(K) contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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Meet Eloquent AIAt Eloquent AI, we’re building the next generation of AI Operators—multimodal, autonomous systems that execute complex workflows across fragmented tools with human-level precision. Our technology goes far beyond chat: it sees, reads, clicks, types, and makes decisions—transforming how work gets done in regulated, high-stakes environments.We’re already powering some of the world’s leading financial institutions and insurers, fundamentally changing how millions of people manage their finances every day. From automating compliance reviews to handling customer operations, our Operators are quietly replacing repetitive, manual tasks with intelligent, end-to-end execution.Headquartered in San Francisco with a global footprint, Eloquent AI is a fast-growing company backed by top-tier investors. Join us to work alongside world-class talent in AI, engineering, and product as we redefine the future of financial services.Your RoleAs a Lead Engineer at Eloquent AI, you will lead the development of AI-powered full-stack applications while overseeing and mentoring other engineers. You’ll remain hands-on across the stack, but also take ownership of technical direction, code quality, and delivery standards.You’ll work closely with engineers, AI researchers, and product teams to ensure scalable, reliable systems that power real-time AI-driven workflows. This role requires strong engineering fundamentals, leadership capability, and the ability to operate effectively in a fast-paced, AI-first environment.You will:Design and build full-stack applications that power AI-driven workflows for enterprise users.Oversee and review the work of other engineers, ensuring high-quality, production-ready code.Provide technical guidance, architectural direction, and hands-on support where needed.Develop high-performance front-end interfaces for AI agent control, monitoring, and visualisation.Build scalable backend services that support real-time AI interactions, knowledge retrieval, and automation.Work closely with AI researchers and ML engineers to integrate LLMs, RAG, and automation into production-ready systems.Establish engineering best practices across testing, deployment, and performance optimisation.Continuously iterate and refine AI-driven products, balancing speed with robustness.Requirements8+ years of hands-on experience building full-stack production applications.Prior experience leading or mentoring engineers.Proficiency in React, TypeScript, and Node.js.Backend experience using Python.Strong knowledge of cloud infrastructure (AWS, GCP, or Azure) and scalable architectures.Understanding of AI-powered applications (LLMs, chat interfaces, agentic workflows).Ability to work in a fast-paced, high-autonomy environment.Strong collaboration skills across engineering, product, and AI teams.Bonus Points If…You have experience building AI-powered applications with LLM integrations.You’ve worked in high-performance startups or enterprise AI environments.You have a sharp eye for UI/UX design and have built intuitive, AI-driven interfaces.You have experience with GraphQL, WebSockets, or real-time data streaming.You’ve contributed to open-source projects or have built developer tools for AI.

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About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.Position Overview Xaira is seeking enthusiastic and motivated candidates to join our team as Research Engineers. We welcome candidates across the spectrum of experience. Teams thrive when they are diverse (across all axes), and we encourage all eligible applicants to apply.  The role is based in our London office, located near Old Street. Our team is highly collaborative, operating on the belief that hard problems are best solved by multiple people working towards a clear goal, bringing and sharing their expertise with the team. We operate a hybrid working culture based on trust. Members of the team are typically in the office 3 days a week. Key Responsibilities Industry experience as a research engineer, in an AI-related company. Excited to work, learn and teach within a collaborative team working on challenging problems. Desirable Below is a list of qualities/experiences that align with the kinds of things that we are looking for. Please do not read this as an extension of the “requirements” section! We recognise that experiences, opportunities and life-paths vary. Masters (or equivalent)/PhD in AI-related field. Public codebases or contribution to public GitHub repositories. Experience building and training neural networks. Experience in distributed training and inference. Experience profiling and optimising large-scale AI models. Knowledge or experience in BioAI. If you are a motivated individual with a passion for applying AI to advance drug discovery and improve human health, we encourage you to apply and join us in our mission to make a positive difference in the world. Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end. TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is accelerating the future of AI and high-performance compute by building industry-leading CPU and AI architectures. As an Automotive and Robotics SoC Architect, you will define scalable, top-down system architectures that unify our CPU and AI technologies for next-generation automotive applications. This senior technical role shapes the architectural direction of our automotive and robotics portfolio, ensuring our products meet the industry's highest expectations for performance, safety, reliability, and security. This position is central to how Tenstorrent delivers world-class automotive solutions and requires strong technical leadership, systems thinking, and cross-functional collaboration. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are A systems thinker who can architect complex SoCs from concept to execution. A strong communicator who can articulate technical direction across engineering teams and external partners. Someone with deep knowledge of safety-critical systems and the unique needs of automotive environments. An innovator who can identify future use cases and propose next-generation architectural solutions. A leader who thrives in a highly technical, cross-functional, fast-moving environment.   What We Need Bachelor’s, Master’s, or Ph.D. in Electrical Engineering, Computer Engineering, or related field. Extensive experience designing complex SoCs, ideally in automotive applications. Proficiency in hardware description languages such as Verilog or VHDL. Experience with hardware/software co-design and co-verification. Knowledge of automotive safety standards (e.g., ISO 26262) and security principles. Someone comfortable with up to 25% international travel.  Experience with both cameras, sensors, and others is a plus.   What You Will Learn How cutting-edge CPU and AI architectures are adapted for automotive-grade environments. Best-in-class methodologies for safety-critical SoC design, verification, and system integration. How to translate emerging automotive use cases into scalable, future-proof SoC architectures. Approaches to hardware-level security, robustness, and cyber-resilience in automotive compute systems. Cross-functional collaboration strategies that drive innovation across architecture, software, DV, and product teams.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Company OverviewDeepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.Company Operating RhythmAt Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.OpportunityDeepgram is looking for a backend software engineer to lead the design and implementation of Deepgram’s Voice Agent product. You will design and implement secure, robust, and scalable services for speech processing; build integrations supporting telephony providers, RAG systems, and diverse deployment scenarios; engineer for testability and observability within a complex chain of AI models; and more. Your skill at building highly reusable code that overcomes technical challenges is paired with an intuition for delightful user experiences. You will be a critical voice in Deepgram’s Product and Engineering teams, driving high impact products from start to finish.What You’ll DoImprove Deepgram’s core inference services including areas in networking, speech processing, model orchestration, and observabilityDevelop integrations with cutting edge in-house, third-party, and open-source AI models for perception and managing conversational dynamicsDebug complex system issues that include networking, scheduling, and highly concurrent workloadsRapidly customize backend services to support our customer needsPartner with Product to design and implement new services, features, and/or products end to endYou’ll Love This Role If YouThrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessityEnjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design workIt’s Important To Us That You Have3+ years of experience in an industry roleProgramming experience in Rust (or C, C++), with competence in PythonExcellent communication and organizational skills, both written and verbal.A high level of experience and understanding of version control; preferably git.Comprehensive experience with UNIX-style systems.It Would Be Great If You HadExperience with low-latency, multi-model orchestration for AI-enabled applicationsExperience with audio processingBenefits & Perks*Holistic healthMedical, dental, vision benefitsAnnual wellness stipendMental health supportLife, STD, LTD Income Insurance PlansWork/life blendUnlimited PTOGenerous paid parental leaveFlexible schedule12 Paid US company holidaysQuarterly personal productivity stipendOne-time stipend for home office upgrades401(k) plan with company matchTax Savings ProgramsContinuous learningLearning / Education stipendParticipation in talks and conferencesEmployee Resource GroupsAI enablement workshops / sessions*For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible.Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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About HandshakeHandshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feelWork hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsJoin a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among othersBuild a massive, fast-growing business with billions in revenueAbout the RoleWe’re expanding our team and seeking a Senior Engineering Manager to lead our Reinforcement Learning Environments (RLE) team.The RLE team builds the sandbox environments where frontier AI models learn complete, end-to-end workflows. These environments simulate real-world professional domains such as software engineering, finance, and legal research — complete with realistic tools, constraints, and feedback loops. Instead of learning from static examples, models practice doing the work: navigating multi-step tasks, using domain-specific tools, handling ambiguity, and optimizing for real outcomes.Researchers use these environments and the data they generate to train state-of-the-art models with reinforcement learning grounded in execution — not just prediction, but task completion, quality, and robustness in complex workflows.As a Senior Engineering Manager, you’ll shape the technical direction and long-term strategy of this critical platform. You’ll lead a growing team (currently 9 engineers) and will likely manage an Engineering Manager in the near term. This is a highly strategic role sitting at the intersection of platform engineering, applied AI infrastructure, research tooling, and human-in-the-loop operations systems.Location: San Francisco, CA| 5 days/week in-officeLead and grow a high-performing team of 8–9 engineers building reinforcement learning environmentsManage, mentor, and develop senior engineers and future engineering leadersPartner closely with research, product, and operations teams to define roadmap and execution prioritiesDrive technical architecture for scalable, reliable, and extensible environment systemsBuild plug-and-play environments that integrate seamlessly with model training pipelinesBalance platform rigor with operational complexity and data quality requirementsEstablish engineering best practices around reliability, observability, and performanceFoster a culture of ownership, velocity, and high technical standardsDesired Capabilities3+ years of engineering management experience, with increasing scope and ownershipExperience managing senior engineers; experience managing an Engineering Manager (or equivalent scope) strongly preferred5+ years of prior hands-on engineering experienceStrong technical background in platform systems, distributed systems, or full-stack infrastructureExperience building internal platforms, data pipelines, or research-facing toolsProven ability to operate effectively in fast-paced, ambiguous environmentsExperience driving cross-functional alignment across engineering, research, and operationsWillingness to work in-office in San Francisco 5 days/weekExtra CreditExperience in reinforcement learning, simulation systems, or AI training infrastructureBackground in human-in-the-loop systems, data annotation platforms, or workflow toolingExperience in operations-heavy, tech-enabled organizationsFamiliarity with cloud infrastructure (AWS or GCP), APIs, and modern web stacks (e.g., React, TypeScript, Node.js, Python)Experience building systems used by AI researchers or applied ML teamsWhat Success Looks LikeRLE becomes the default platform researchers use to train reinforcement learning workflowsNew domains (e.g., finance, legal, SWE) can be launched quickly and reliablyEnvironment reliability and data quality are trusted by top AI research partnersThe team scales with strong technical leaders who can independently drive new verticalsThe RLE platform materially accelerates model capability in real-world task completionPerksHandshake delivers benefits that help you feel supported—and thrive at work and in life.The below benefits are for full-time US employees.🎯 Ownership: Equity in a fast-growing company💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching🍼 Family Support: Paid parental leave, fertility benefits, parental coaching💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

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About the Role The Turbo team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale. Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design. You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal. Requirements We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay. You might be a good fit if you: Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others: Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving. RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models. Model architecture design for Transformers or other large neural nets. Distributed systems / high‑performance computing for ML. Are comfortable working from algorithms to engines: Strong coding ability in Python Experience profiling and optimizing performance across GPU, networking, and memory layers. Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack. Have a solid research foundation in your area(s) of depth: Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems). Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API). Operate well as a full‑stack problem solver: You naturally ask: “Where in the stack is this really bottlenecked?” You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins. Minimum qualifications 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source). Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience. Demonstrated experience owning complex technical projects end‑to‑end. If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement. Responsibilities Advance inference efficiency end‑to‑end Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference. Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc. Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost. Unify inference with RL / post‑training Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems. Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper. Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack. Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers. Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design. Own critical systems at production scale Profile, debug, and optimize inference and post‑training services under real production workloads. Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed. Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously. Provide technical leadership (Staff level) Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training. Mentor other engineers and researchers on full‑stack ML systems work and performance engineering. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy    

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About EmaEma is at the forefront of the agentic AI revolution, empowering enterprises to reimagine how work gets done. Our platform enables organizations to design, deploy, and manage fleets of AI employees—multi-agent systems with rich human-in-the-loop interfaces—that automate complex workflows, augment decision-making, and unlock new levels of efficiency and growth. We are a team of ambitious innovators, building the future of work, and we’re looking for passionate individuals to join us on this mission.The RoleThis is not a traditional, backlog-focused product management role. As an Agentic Solutions Product Manager, you’ll partner directly with enterprise leaders to observe and decode human workflows—what data they use, what applications they rely on, and what SOPs they follow. From this, you’ll craft AI employees: multi-agent workflows with intuitive, UI-driven human-in-the-loop controls that transform how businesses operate.You won’t just manage features; you’ll design and deliver entire AI-powered solutions. You’ll be a trusted advisor and a strategic co-creator, working at the intersection of business strategy, workflow design, and cutting-edge AI technology.What You Will DoUnderstand Human Workflows: Partner with enterprise customers to map end-to-end processes, uncover inefficiencies, and identify opportunities where agentic AI can create impact.Design AI Employees: Translate workflows into agentic multi-agent systems, integrating data, applications, and UI-driven human oversight.Bridge Business and Technology: Work hand-in-hand with engineering and design to turn client requirements into scalable agent capabilities and elegant product experiences.Drive Strategic Roadmaps: Own the lifecycle of your AI employees—from concept through deployment—guided by customer feedback, data, and business outcomes.Champion Adoption & Value: Ensure customers achieve measurable ROI, advocate for your solutions internally and externally, and evangelize the power of agentic AI.Continuously Optimize: Use data and customer insights to refine workflows, enhance capabilities, and identify new areas for automation and transformation. What We’re Looking ForEntrepreneurial Mindset: Self-starter who thrives in ambiguity, owns outcomes, and builds solutions from the ground up.Proven Client-Facing Experience: 4+ years in consulting, engagement management, product, or as a founder—trusted by senior stakeholders.Strategic Product Acumen: Ability to go beyond surface-level requests and solve the real business problem.Technical Credibility: Comfortable diving into architectural trade-offs, APIs, and agentic design with engineers.Systems Thinking: Natural ability to see the whole picture, anticipate downstream effects, and design resilient solutions. Preferred SkillsExperience in user research and workflow mapping, with a data-driven mindset.Familiarity with generative AI and agentic AI; hands-on experience designing agent-based systems is a plus.Ability to prototype quickly—comfortable with "vibe coding" to visualize solutions.Background in product management, consulting, or founding roles.Experience in agile development environments and tools (JIRA, Asana, etc.).Hands-on experience with APIs and working closely with technical teams.Degree in Computer Science, Engineering, Math, or equivalent experience. For California Based CandidatesThe standard base salary for this position is $135,000 to $200,000 annually.Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.