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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking for:We’re looking for curious and intellectually proactive contributors, the kind of person who double-checks assumptions and plays devil’s advocate. Are you comfortable with ambiguity and complexity? Does an async, remote, flexible opportunity sound exciting? Would you like to learn how modern AI systems are tested and evaluated?This is a flexible, project-based opportunity well-suited for:Analysts, researchers, or consultants with strong critical thinking skills.Students (senior undergrads / grad students) looking for an intellectually interesting gig.People open to a part-time and non-permanent opportunity. About the project:We’re on the hunt for QAs for autonomous AI agents for a new project focused on validating and improving complex task structures, policy logic, and agent evaluation frameworks. Throughout the project, you’ll have to balance quality assurance, research, and logical problem-solving. This project opportunity is ideal for people who enjoy looking at systems holistically and thinking through scenarios, implications, and edge cases.You do not need a coding background, but you must be curious, intellectually rigorous, and capable of evaluating the soundness and consistency of complex setups. If you’ve ever excelled in things like consulting, CHGK, Olympiads, case solving, or systems thinking — you might be a great fit.What you’ll be doing:Reviewing evaluation tasks and scenarios for logic, completeness, and realism.Identifying inconsistencies, missing assumptions, or unclear decision points.Helping define clear expected behaviors (gold standards) for AI agents.Annotating cause-effect relationships, reasoning paths, and plausible alternatives.Thinking through complex systems and policies as a human would to ensure agents are tested properly.Working closely with QA, writers, or developers to suggest refinements or edge case coverage.How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsExcellent analytical thinking: Can reason about complex systems, scenarios, and logical implications.Strong attention to detail: Can spot contradictions, ambiguities, and vague requirements.Familiarity with structured data formats: Can read, not necessarily write JSON/YAML.Ability to assess scenarios holistically: What's missing, what’s unrealistic, what might break?Good communication and clear writing (in English) to document your findings. We also value applicants who have:Experience with policy evaluation, logic puzzles, case studies, or structured scenario design.Background in consulting, academia, olympiads (e.g. logic/math/informatics), or research.Exposure to LLMs, prompt engineering, or AI-generated content.Familiarity with QA or test-case thinking (edge cases, failure modes, “what could go wrong”).Some understanding of how scoring or evaluation works in agent testing (precision, coverage, etc.).BenefitsGet paid for your expertise, with rates that can go up to $45 hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.About the Role: Glean is seeking a talented AI Outcomes Manager to join our rapidly expanding team. The AI Outcomes Manager will play a crucial role in transforming how every department works, with the power of Glean. They will work closely with executives and end users, combining business acumen, product sense, and prompting skills to help them transform into an AI-native enterprise. You will: Partner with executive sponsors and end users to identify high‑impact use cases and turn them into measurable business outcomes on Glean. Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Glean’s platform. Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities. Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform. Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. Proactively identify expansion opportunities and drive engagement across teams and functions. About you: 5+ years of professional experience in roles that blend business and technology (e.g., product, analytics, data, engineering, solutions), with a consultative, customer‑facing approach. Strong problem‑solving and communication skills; comfortable working with stakeholders from ICs to executives and tailoring messages to different audiences. Demonstrated ability to craft effective prompts and guide AI agents for real customer or business workflows; you’ve shipped outcomes, not just demos. Understanding of what current LLMs can and cannot do; able to set expectations and steer towards reliable, safe, cost‑effective solutions. Product sense and user empathy—you can spot high‑value applications of AI across diverse job functions and design clear, guided experiences. Hands‑on experience with modern AI platforms and tools (e.g., OpenAI, Claude, Mistral, Cohere or similar), with enough technical depth to work with engineers without needing to be on the critical path for writing production code. Good to have: Prior experience in customer‑facing, consultative roles (solutions, support, product management) and comfort presenting to senior leaders. Exposure to evaluating AI outcomes (e.g., defining success criteria, using sample tasks, reviewing results) and iterating for quality, latency, and cost. Ability to analyze usage signals and customer feedback to inform roadmap and drive adoption. Location:  This role is hybrid (3-4 days a week in one of our SF Bay Area offices) Compensation & Benefits: The standard OTE range for this position is $150,000-$212,000 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. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. California Consumer Privacy Act (CCPA) Notice

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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. California Consumer Privacy Act (CCPA) Notice

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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 Full-Stack Engineer at Eloquent AI, you will be at the forefront of building and scaling AI-powered applications, transforming how enterprises interact with intelligent agents. You’ll work across the entire stack, developing high-performance front-end experiences and scalable back-end systems that power real-time AI-driven workflows.This role requires strong software engineering skills, a deep understanding of full-stack development, and the ability to work in a fast-paced, AI-first environment. You’ll collaborate with engineers, AI researchers, and product teams to build enterprise-grade solutions that enable seamless AI-human interactions.You will:Design and build full-stack applications that power AI-driven workflows for enterprise users.Develop high-performance front-end interfaces for AI agent control, monitoring, and visualization.Build scalable backend services that support real-time AI interactions, knowledge retrieval, and automation.Optimize AI-powered UIs to ensure seamless and intuitive user experiences.Work closely with AI researchers and ML engineers to integrate LLMs, Retrieval-Augmented Generation (RAG), and automation into production-ready applications.Ship robust, minimal-dependency code that performs efficiently in enterprise environments.Continuously iterate and refine AI-driven products, balancing user needs with technical feasibility.Requirements7+ years of hands-on experience building full-stack production applications.Proficiency in modern web technologies, including React, TypeScript, and Node.js.Experience with backend development using Python.Strong knowledge of cloud infrastructure (AWS, GCP, or Azure) and scalable architectures.Understanding of AI-powered applications, including LLMs, chat interfaces, and agentic workflows.Ability to work in a fast-paced, high-autonomy environment, solving complex problems and delivering impact.Strong collaboration skills, with experience working in cross-functional teams with engineers, designers, and AI researchers.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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Who are we?Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the Universal AI employee. We are founded by ex-Google, Coinbase, Okta executives, and serial entrepreneurs. We’re well-funded by the top investors and angels in the world. Ema is based in Silicon Valley and Bangalore. Who are you?The Senior AI Application Engineer will be pivotal in providing world-class post-deployment support for Ema’s Agent Assist/Chatbot product. This role requires a strong blend of technical expertise and customer-focused problem-solving. You will configure, troubleshoot, and optimize AI solutions for our customers, ensuring high performance, continuous improvement of customer workflows, and exceptional customer satisfaction. You will independently manage complex deployments and solutions for enterprise customers with minimal guidance.You will:Roles and ResponsibilitiesConfigure and integrate AI/GenAI workflows using platform APIs and customer data, ensuring smooth and secure deployment.Translate customer requirements into technical solutions, validating workflow correctness and continuously refining prompts for optimal performance.Develop and automate tasks using Python & SQL, and build prototypes using open-source Agentic Frameworks to streamline CX workflows.Design, run, and analyze A/A experiments to measure and improve workflow quality and reliability.Monitor AI workflows using business metrics and observability dashboards, quickly responding to issues to ensure high availability.Provide proactive solutions and regular updates to customers, maintaining high CSAT through effective troubleshooting and communication.Diagnose and resolve platform issues related to APIs, data integration, and workflow configurations, collaborating with engineering when needed.Utilize APIs and integration protocols (JSON, REST, SOAP) to configure workflows and integrate with CRM/ATS tools.Write custom scripts to query databases and create reports for in-depth analysis and to demonstrate ROI to customers.Ideally, you'd have:Experience:4+ years of software engineering experience.Significant experience in AI/LLM application development, including building agents, integrations, workflows, and evaluating/improving their performance.Experience setting up, configuring, and supporting ML Systems or AI Agents is a plus.Experience in building LLM-based evaluation frameworks & conducting UATs with real customers.Experience with prompt engineering techniques.Demonstrated the ability to manage complex deployments & solution design for an enterprise customer independently with minimal guidance.Familiarity with key support metrics (FRT, AHT, TAT, CSAT) and reporting.Strong troubleshooting and problem-solving skills, especially in production environments. Ideal candidates should be able to troubleshoot ML performance issues & recommend solutions to improve accuracy metrics & other business KPIs.Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders.Technical Skills:Proficiency in Python & SQL scripting.Understanding of Data Structures & Algorithms is a plus.Experience with prompt engineering techniques.Proficient at invoking platform APIs to retrieve or push data, configure workflows.Familiarity with JSON, REST, SOAP or other integration protocols. Familiarity with integrating common CRMs/ATS tools would be a plus.Data-driven evaluation skills, including setting up and interpreting A/A experiments.Familiarity with logging, dashboard creation, and alerting tools.Soft Skills:Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders.Demonstrated ability to manage complex deployments & solution design for an enterprise customer independently.Strong troubleshooting and problem-solving skills, especially in production environments.Ownership & Initiative: Takes responsibility for ongoing workflow management and customer outcomes.Curiosity & Continuous Learning: Actively explores new GenAI/automation techniques and best practices to enhance workflows.Collaboration: Works effectively across multiple teams.Customer Empathy: Prioritizes customer success criteria, ensuring solutions address real business needs.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.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 700+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewWe’re looking for a technical, systems-minded operator to build and scale the evaluation engine behind Harvey’s platform. As we expand globally, ensuring our models behave reliably, accurately, and jurisdictionally correctly is mission-critical—and evaluation complexity is increasing 10x.As a member of our Product Operations team, you’ll work closely with Applied Legal Researchers, Product, Engineering, AI Research, and human data providers to operationalize evaluation methodologies and embed them into our product development lifecycle. You’ll create the workflows, systems, and tooling that make evaluation a first-class product capability at Harvey.This is a high-ownership role for someone who thrives in ambiguity, loves building structure from ambiguity, and wants to help scale the evaluation infrastructure of a global AI company.What You’ll DoBuild and scale the systems that power model and product evaluations across HarveyEmbed evaluation workflows and readiness checkpoints into the product development lifecycleCreate the single source of truth for evaluation status, results, history, and launch readinessTurn Expert-designed evaluation methodologies into scalable, repeatable operational processesManage relationships with human data vendors and ensure evaluation quality meets legal standardsWork with Engineering and Research to improve evaluation tooling, automation, and dashboardsDrive evaluation readiness for major product and model launches across geographies and jurisdictionsDocument and operationalize evaluation governance as complexity increasesHelp define how Harvey ensures model accuracy, reliability, and trust at global scaleWhat You Have4–7+ years in technical program management, product operations, research operations, or evaluation/benchmarking rolesExperience working with ML/AI evaluations, benchmarking frameworks, or scientific workflowsComfort with statistical methodologies and SQL or Python, or similar tools to interpret evaluation dataAbility to work deeply with legal experts and operationalize complex evaluation methodologiesStrong cross-functional coordination skills across Product, Engineering, Research, and data providers/vendorsHigh attention to detail and a bias toward clarity, rigor, and reproducibilityAbility to navigate extreme ambiguity and bring order to complex systemsStrong communication skills and comfort translating technical nuance for diverse stakeholdersDesire to do whatever it takes to make evaluation systems successful—from writing documentation to diagnosing pipeline issuesBonus PointsExperience in legal tech or working with domain experts in regulated industriesExperience managing human data providers or human-in-the-loop evaluation pipelinesBackground in ML research, data quality management, or evaluation scienceEarly employee at a hyper-growth startupExperience at world-class product or platform operations orgs (ex: Stripe, Ramp)Compensation$178,500 - $210,000 USDPlease find our CA applicant privacy notice here.#LI-CL1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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Why join Heidi Health?🧘‍♂️ Additional paid day off for your birthday and wellness days🎓 A generous personal development budget of $500 per annum🧠 Learn from some of the best engineers and creatives, joining a diverse team🌏 The rare chance to create a global impact as you immerse yourself in one of Australia’s leading healthtech startups🚀 If you have an impact quickly, the opportunity to fast track your startup career!🩺 Help us reimagine primary care and change the face of healthcare in Australia and then around the world.About Your RoleWhat You’ll DoArchitect and build backend services that power LLM-based agents and clinical automations.Design robust APIs & data models that are secure, observable and easy for other teams to extend.Optimise performance and cost—profile hot paths, tune databases and right-size cloud resources.Automate quality: write unit / integration tests, craft alerts and own on-call runbooks so clinicians can trust every interaction.Partner with product, AI and front-end engineers to ship new capabilities from concept to production in weeks, not quarters.What We’re Looking ForMastery of software-engineering fundamentals; Python is our primary language, but you move fluently between technologies when the problem demands.Proven experience designing APIs (REST or GraphQL), and event-driven systems (Kafka, Pub/Sub or similar).Deep coding and architect mindset — Hands on experience in test driven development (TDD), AI coding, microservices, eventual consistency etc.Deep database expertise—schema design, query optimisation and scaling for both relational and NoSQL stores.Cloud fluency (GCP or AWS): containers, CI/CD, infrastructure-as-code, security and observability.Track record of shipping and operating distributed systems at scale with high reliabilityRigorous testing, code-review and documentation habits that elevate team standards.Hands-on work with AI/LLM services or real-time audio/streaming pipelines.What do we believe in?Heidi builds for the future of healthcare, not just the next quarter, and our goals are ambitious because the world’s health demands it. We believe in progress built through precision, pace, and ownership.Live Forever - Every release moves care forward: measured, safe, and built to last. Data guides us, but patients define the truth that matters.Practice Ownership - Decisions follow logic and proof, not hierarchy. Exceptional care demands exceptional standards in our work, our thinking, and our character.Small Cuts Heal Faster - Stability earns trust, speed delivers impact. Progress is about learning fast without breaking what people depend on.Make others better - Feedback is direct, kindness is constant, and excellence lifts everyone. Our success is measured by collective growth, not individual output.Our mission is clear: expand the world’s capacity to care, and do it without losing the humanity that makes care worth delivering.Who are Heidi?Heidi is building an AI Care Partner that supports clinicians every step of the way, from documentation to delivery of care.We exist to double healthcare’s capacity while keeping care deeply human. In 18 months, Heidi has returned more than 18 million hours to clinicians and supported over 73 million patient visits. Today, more than two million patient visits each week are powered by Heidi across 116 countries and over 110 languages.Founded by clinicians, Heidi brings together clinicians, engineers, designers, scientists, creatives, and mathematicians, working with a shared purpose: to strengthen the human connection at the heart of healthcare.Backed by nearly $100 million in total funding, Heidi is expanding across ANZ, the USA, UK, Canada, and Europe, partnering with major health systemsWe move quickly where it matters and stay grounded in what’s proven, shaping healthcare’s next era. Ready for the challenge?

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Exa is building a search engine from scratch to serve every AI application. We build massive-scale infrastructure to crawl the web, train state-of-the-art embedding models to index it, and develop super high performant vector databases in Rust to search over it. We also own a $5M H200 GPU cluster that regularly lights up tens of thousands of machines.As a Data Engineer, you'll architect and build the data infrastructure that powers everything we do—from crawling billions of pages to training our embedding models to serving real-time search. You'll have enormous autonomy in designing systems that scale to hundreds of petabytes. If you've ever wanted to build data pipelines at a scale that most companies only dream about, this is your chance.Desired ExperienceDeep understanding of lakehouse architectures (Delta Lake, Iceberg, Hudi) and when to use themExperience building and operating large-scale distributed data processing pipelinesHands-on experience with streaming data systems (Kafka, Flink, or similar)Familiarity with Ray, Spark, or ClickHouse at production scaleAn obsessive focus on reliability and building systems that don't page you at 3amBonus PointsExperience with Lance or other vector-native storage formatsBackground in GPU-accelerated data processing (RAPIDS, cuDF)Example ProjectsDesign a lakehouse architecture that handles 100+ PB of web crawl dataBuild streaming pipelines that process billions of documents per day for real-time indexingArchitect the data layer for our embedding training infrastructure on RayScale our ClickHouse deployment to handle analytical queries across petabytes of search logsThis is an in-person opportunity in San Francisco. We're happy to sponsor international candidates (e.g., STEM OPT, OPT, H1B, O1, E3).

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About The Role:We are hiring our first Partner Solutions Architect to help define how partners and enterprises adopt agentic AI using LangChain, LangGraph, and LangSmith.This is a hands on technical role working closely with cloud providers, system integrators, and technology partners to build integrations, reference architectures, and production ready demos. You will work at the intersection of engineering, product, partnerships, and GTM, translating partner and customer needs into scalable technical solutions.What You’ll Do:Partner with cloud providers, system integrators, and ISVs to design and build agentic AI solutions.Create production ready solutions, sample repositories, and reference architectures using LangChain, LangGraph, and LangSmith.Collaborate closely with product and engineering teams to support partner integrations and solution design.Enable partners through technical workshops, solution walkthroughs, and hands on collaboration.Gather partner and customer feedback and translate it into actionable insights for product and integration roadmaps.How to Be Successful in the Role:5 or more years in technical, customer or partner facing roles such as Solutions Architect, Sales Engineer, Forward Deployed Engineer, DevRel, or Applied AI Engineer.Strong Python skills and experience building and deploying solutions on cloud platforms, with AWS preferred.Experience working with LLMs, RAG, agents, orchestration frameworks, or ML infrastructure.Ability to collaborate effectively with external partners on complex technical projects.Strong communication skills and comfort explaining technical concepts to both technical and non technical audiences.Start up DNA - the ability to thrive in a fast paced, scaling environment.Experience taking generative AI or agent based systems from prototype to production, preferred.Hands on experience with LangChain, LangGraph, LangSmith, or similar agent frameworks, would be a big bonus.Background in cloud native architectures including serverless, containerized, or VPC based deployments, preferred.Prior open source contributions or technical content creation, would be a bonus. Compensation and Benefits:We offer competitive compensation including base salary, equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Compensation varies based on role, level, and location.Annual salary range: $170,000 to $200,000 USD

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About the role:LangChain is hiring an Education Engineer to help developers and agent builders learn how to build, evaluate, and continuously refine agents using LangSmith. In this role, you’ll turn cutting-edge applied AI techniques into accessible, engaging educational content across multiple formats - from online courses to in-person meetups and workshops.You will collaborate with our Applied AI and engineering teams to create high-quality learning experiences that explain core concepts in agentic AI evaluation, monitoring, and iterative refinement. You will guide developers through real-world examples, showcase (and develop) best practices, and help the community succeed with LangChain tools. This is a hybrid role that blends technical machine learning experience with a passion for education, community building, and communication.LangChain is uniquely positioned in the industry with the leading Agent Tracing, Evaluation, and Monitoring platform paired with the most vibrant agent developer community. This tight coupling enables developers to overcome the most significant hurdle in deploying agents today: reliability. We need an educator who can understand and communicate these advantages to the community.What you’ll do:Collaborate with LangChain engineers to develop educational content that teaches agentic evaluation, monitoring and refinement using LangSmith, LangChain and LangGraph.Design curriculum and structured learning paths for our community of over 1 million developers and agent builders.Create and deliver content across multiple formats:Online courses for LangChain Academy, video tutorials, and webinarsLive presentations at workshops, hackathons, meetups, and conferencesBuild and maintain example projects, code demos, and visuals to support educational content.Translate experimental applied AI code and internal agent evaluation techniques into crisp, developer-friendly learning materials.How to be successful in the role:A technical background and domain expertise in applied AI (Machine Learning, LLMs etc). You should be comfortable using datasets to run experiments, analyze model performance, and iterate toward more reliable, higher-quality outcomes.2+ years experience as a software engineer/developer who enjoys and excels at making technical concepts understandable.Previous experience developing online asynchronous curriculum in the areas of GenAI, AI, machine learning, data science, robotics, or similar.Strong working knowledge of generative AI concepts, agents, and agent evaluation.A clear, engaging communication style - both written and on camera.Experience designing and teaching technical content for developers (courses, workshops, or technical onboarding).Familiarity with LangChain, LangSmith or similar LLM frameworks/tools is a strong plus.A degree in Computer Science, Machine Learning, Math, Data Science, and/or equivalent industry experienceCompensation and Benefits:We offer competitive compensation including base salary, equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Compensation varies based on role, level, and location. Annual salary range: $155,000 - 185,000

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About Us Observe.AI is the leading AI agent platform for customer experience. It enables enterprises to deploy AI agents that automate customer interactions, delivering natural conversations for customers with predictable outcomes for the business. Observe.AI combines advanced speech understanding, workflow automation, and enterprise-grade governance to execute end-to-end workflows with AI agents. It also enables teams to guide and augment human agents with AI copilots, and analyze 100% of human and AI interactions for insights, coaching, and quality management. Companies like DoorDash, Affordable Care, Signify Health, and Verida use Observe.AI to transform customer experiences every day by accelerating service speed, increasing operational efficiency, and strengthening customer loyalty across every channel. Why Join Us We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization. You’ll own the end-to-end lifecycle of AI agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance. What you’ll be doing Build & Deploy Agents: Own the full AI agent build process - prompts, workflows, integrations, telephony setup, and evaluation forms. Client Engagement: Lead weekly demos, show progress, gather feedback, and act as the primary technical point of contact once a solution is defined. Systems Integration: Configure APIs, data maps, authentication, error handling, and connect to CRMs, databases, or knowledge systems. Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality. Optimization: Monitor performance, refine prompts, test iteratively, and ensure agents meet automation and containment targets. Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion. Shadow Core Engineering: Collaborate with product/engineering teams for deep technical fixes and platformization, while independently leading client delivery. What you'll bring to the role 3+ years in conversational AI, ML engineering, or system integration with hands-on delivery of AI/LLM-based solutions. Strong skills in prompt engineering, workflow building, API integration, and telephony (SIP, Twilio, Amazon Connect, etc.). Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.). ML expertise in embeddings, retrieval-augmented generation (RAG), evaluation frameworks, fine-tuning models, and performance optimization. Solid programming skills (Python, JavaScript, or similar). Comfort leading customer-facing discussions - from deep technical troubleshooting to weekly project demos. Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems. Bachelor’s degree in Computer Science, Engineering, or a related technical field Hands-on experience with Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficient in API integrations and data flow management. Strong experience in telephony integrations, including knowledge of protocols like SIP, PSTN, and other telephony technologies. Perks & Benefits Competitive compensation including equity Excellent medical, dental, and vision insurance options Flexible time off  10 Company holidays + Winter Break and up to 16-weeks of parental leave 401K plan Quarterly Lifestyle Spend Monthly Mobile + Internet Stipend Pre-tax Commuter Benefits Salary Range The base salary compensation range targeted for this full-time position is $108 - 170K per annum. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives and equity (in the form of options). This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. Our Commitment to Inclusion and Belonging Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply. If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.  #LI- Redwood City, CA (Hybrid)

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A1 is a self-funded AI group, operating in full stealth. We’re building a new global consumer AI application where iOS is a core platform, not an afterthought.This is a founding iOS role. You’ll design AI-powered mobile systems that balance UX excellence with the realities of AI latency, streaming, and failure modes.Why This Role MattersYou define how AI feels in users’ handsYou bridge backend intelligence with human interactionYou help establish iOS engineering standards from zeroYou influence product direction through what’s possible on-deviceWhat You’ll DoBuild and maintain iOS apps using Swift / SwiftUIIntegrate AI-powered features via backend APIsImplement camera, microphone, and media pipelinesDesign UX for AI interactions (loading, streaming, retries, fallbacks)Optimize performance, memory, and battery usageCapture user feedback and signals for AI evaluationCollaborate with backend and AI teams on API designMaintain high App Store quality and production stabilityWhat It’s Like to Work HereYou own features end-to-endYou design systems, not just screensYou think deeply about latency, reliability, and UX tradeoffsYou move fast, test in production, and iterateYou work closely with senior engineers and foundersRequirements3+ years of iOS development experience (Swift)Hands-on experience integrating AI featuresStrong understanding of async/await and background tasksExperience with camera, audio, and local storageSolid iOS performance and memory optimization skillsExperience shipping production appsNice to HaveExposure to CoreML or on-device MLBuilt AI chat, voice, or streaming-based appsExperience with feature flags or remote configStrong intuition for AI UX patternsOur Team & CultureWe operate as a dense, senior, high-performance team. We value clarity, speed, craftsmanship, and relentless ownership. We behave like founders — we build, ship, iterate, and hold ourselves to a high technical bar.If you value excellence, enjoy building real systems, and want to be part of a small team creating something globally impactful, you’ll thrive here.About A1A1 is a self-funded, independent AI group, focused on building a new consumer AI product with global impact. We’re assembling a small, elite team of ML and engineering builders who want to work on meaningful, high-impact problems.

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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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About the RoleAs a Software / ML Engineer you will work cross functionally with product, data science and data platform to identify, design and implement the applied ML models and infra, ranging from the model optimization, data pipeline to model training and serving infrastructure, on one of the fastest growing native AI consumer applications on the market today. You will work on implementation of our ML backend systems to power the discovery surfaces including recommendation, ranking and search, supporting new AI generated content formats on our product while working with the team to support optimizing our existing systems.Requirements:B.A.S. in Computer Science or equivalent experience.5+ years of industry experienceExperience building/consuming RESTful and gRPC based web-servicesExperience building and managing infrastructure in a cloud environment (GCP, AWS or Azure)Familiar with one of the popular ML Frameworks like Pytorch, TensorflowExperience writing highly performant service in a modern typed languageExperience configuring and maintaining CI/CD pipelines and automated testingDesired Experience:Experience with shipping intelligent features, end-to-end, and from idea to productionExperience with understanding, designing or implementing a full pipeline from data ingestion to model training.Experience with production AI/ML systems and services including optimizing GPU/TPU deploymentsExperience working with vector databases or other feature storageYou will be a good fit if you are proactive and have a “get things done” mindset. Given our current pace of growth and load on our systems, most people have had a significant impact during their first week at the company.About Character.AICharacter.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI! At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.

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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.About the Role: Glean is seeking a talented AI Outcomes Manager to join our rapidly expanding team. The AI Outcomes Manager will play a crucial role in transforming how every department works, with the power of Glean. They will work closely with executives and end users, combining business acumen, product sense, and prompting skills to help them transform into an AI-native enterprise. You will: Partner with executive sponsors and end users to identify high‑impact use cases and turn them into measurable business outcomes on Glean. Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Glean’s platform. Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities. Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform. Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. Proactively identify expansion opportunities and drive engagement across teams and functions. About you: 5+ years of professional experience in roles that blend business and technology (e.g., product, analytics, data, engineering, solutions), with a consultative, customer‑facing approach. Strong problem‑solving and communication skills; comfortable working with stakeholders from ICs to executives and tailoring messages to different audiences. Demonstrated ability to craft effective prompts and guide AI agents for real customer or business workflows; you’ve shipped outcomes, not just demos. Understanding of what current LLMs can and cannot do; able to set expectations and steer towards reliable, safe, cost‑effective solutions. Product sense and user empathy—you can spot high‑value applications of AI across diverse job functions and design clear, guided experiences. Hands‑on experience with modern AI platforms and tools (e.g., OpenAI, Claude, Mistral, Cohere or similar), with enough technical depth to work with engineers without needing to be on the critical path for writing production code. Good to have: Prior experience in customer‑facing, consultative roles (solutions, support, product management) and comfort presenting to senior leaders. Exposure to evaluating AI outcomes (e.g., defining success criteria, using sample tasks, reviewing results) and iterating for quality, latency, and cost. Ability to analyze usage signals and customer feedback to inform roadmap and drive adoption. Location: This role is remote in the U.S. Compensation & Benefits: The standard OTE range for this position is $130,000-$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. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. #LI-Remote