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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About the Role Snorkel AI is hiring Frontier AI Solutions Engineers who will partner with leading AI labs on their most challenging data problems. This is a high-impact, customer-facing role that combines technical depth with strong presales instincts. You'll partner with customer research teams to design complex data and environments that improve frontier model performance, demonstrating Snorkel's capabilities through research-driven engagements. You'll work at the critical intersection of research, technical strategy, and customer partnership. This includes scoping training data needs, designing RL environments and tasks, developing evaluation frameworks, probing model behavior and failure modes, and translating customer research objectives into actionable technical plans. You'll develop technical specifications, analyze frontier model failure modes, and serve as a thought partner to customer research teams throughout the sales cycle and into early delivery phases. Main Responsibilities Partner with frontier AI research labs to design datasets and environments that improve model performance Lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria Probe model behavior through systematic evaluation to uncover weaknesses and identify high-impact data interventions Design evaluation frameworks, calibration processes, and quality rubrics that establish measurable project success metrics Develop technical specifications for data projects that balance research rigor with operational feasibility Serve as thought partner to customer research teams throughout the sales cycle, building trust and credibility Stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies Preferred Qualifications Strong expertise in frontier AI concepts including LLMs, training data pipelines, evaluation methodologies, post-training techniques (RLHF, DPO, RLAIF), and domain areas such as coding agents, reasoning, multimodal models, or RL environments Experience in applied ML research, data science, or research-intensive technical roles with customer-facing or collaborative research experience Proficiency in Python and familiarity with ML frameworks and LLM APIs Excellent communication skills — ability to deliver technical presentations and explain complex concepts to diverse audiences Familiarity with data curation workflows, synthetic data generation, LLM-as-a-Judge, or evaluation framework design Ability to work in a fast-moving environment, comfortable with ambiguity and rapid iteration B.S. in Computer Science, Machine Learning, or related field with 4+ years of experience in AI/ML solutions engineering or technical customer-facing roles Compensation range for Tier 1 locations of San Francisco Bay Area and New York City, $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Why Join Snorkel AI? At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to own technical data workflows and be a founding member of the technical DaaS team.  #LI-CG1 Salary Range  -   Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!About North:North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.Why This Role?Cohere’s team partners with Canadian public sector organisations to unlock transformative value through secure, ethical deployment of Generative AI (GenAI) solutions. We work collaboratively to address complex societal challenges while maintaining the highest standards of data security and compliance. You will work directly with public sector customers to quickly understand their greatest problems and design and implement solutions using Cohere's stack.This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors.We are seeking engineers with diverse skill sets, including backend, infrastructure, agent development, and deployments, who deeply care about customers and want to work at the cutting edge of Agentic AI.Location: Ottawa or Toronto required (proximity to government customers), 20-40% travel anticipated Security Clearance: Active Top Secret clearance strongly preferred; candidates eligible and willing to obtain clearance will also be consideredIn this role, you will:Build and ship features for North, our AI workspace platformDevelop autonomous agents that talk to sensitive enterprise dataExperiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectationsWork across the entire product lifecycle from conceptualization through productionLead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rolloutYou may be a good fit if:You have experience with and enjoy working directly with customersYou have shipped (lots of) Python in productionYou have built and deployed highly performant client-side or server-side RAG/agentic applicationsYou have strong coding abilities and are comfortable working across the stack. You’re able to read and understand, and even fix issues outside of the main code baseYou excel in fast-paced environments and can execute while priorities and objectives are a moving targetIf some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.About the team Our Public Services Business Unit is committed to leveraging AI for the benefit of individual citizens and the public good. From our work informing strategic government decisions, to optimising our NHS, through to reducing bureaucratic backlogs - we know that AI offers opportunities to drive improvements at every level of Government and we are proud to lead on some of the most impactful work happening in the sector. Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Security Clearance (SC) and willing to work on site with these clients from time to time.About the roleAs a Senior Data Scientist, you will lead high-impact AI projects and shape the technical direction of bespoke solutions. This role requires hands-on technical excellence combined with crucial team leadership. You will define data science approaches, design robust software architectures, mentor junior colleagues, and ensure delivery rigour across projects all while building deep client relationships and solidifying our reputation as a leader in practical, measurable AI.What you'll be doing:Leading project teams that deliver bespoke algorithms and high-stakes AI solutions to clients across the sector.Conceiving the core data science approach and designing the associated robust software architecture for new engagements.Mentoring a small number of data scientists and supporting the professional growth of technical team members on projects.Partnering with commercial teams to build client relationships and shape project scope for technical feasibility.Contributing to Faculty’s thought leadership and reputation through delivering courses, public speaking, or open-source projects.Ensuring best practices are followed throughout the project lifecycle to guarantee high-quality, impactful delivery.Who we're looking for:You possess senior experience in a professional data science position or a quantitative academic field.You demonstrate strong programming skills, with the ability to be a fluent Python programmer, using core libraries (NumPy, Pandas) and a deep-learning framework (e.g., PyTorch).You have a deep expertise in core data science paradigms (supervised/unsupervised, NLP, validation), demonstrating a proficiency across the standard data science toolkit, including the ability to develop new, innovative algorithms.You bring a leadership mindset, focused on growing the technical capabilities of the team and nurturing a collaborative culture.You exhibit commercial awareness, with experience in client-facing work and the ability to translate business problems into a rigorous mathematical framework.You are skilled in project planning, assessing technical feasibility, estimating delivery timelines, and leading a team to deliver high-quality work on a strict schedule.Our Interview ProcessTalent Team Screen (30 minutes)Take Home Technical AssessmentTechnical Interview (90 minutes)Commercial Interview (60 minutes)Our Recruitment EthosWe aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.Some of our standout benefits:Unlimited Annual Leave PolicyPrivate healthcare and dentalEnhanced parental leaveFamily-Friendly Flexibility & Flexible workingSanctus CoachingHybrid WorkingIf you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

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About the RoleYou will architect, build, and scale the internal technology ecosystem that accelerates workforce productivity, eliminates operational friction, and gives the company a compounding infrastructure advantage. You will treat internal tools with the same product rigour and user-centricity as any external product — because the quality of internal systems directly determines organisational velocity.You will lead a cross-functional engineering team, make high-stakes build-vs-buy decisions, and drive AI adoption into internal workflows. This role requires someone who can see the company’s operational architecture as a system design problem and solve it with software.What You Will DoInternal Platform Strategy & RoadmapOwn the end-to-end strategy and roadmap for all internal tools, platforms, and automation — treating internal technology as a product, not a cost centre.Make strategic build-vs-buy decisions, knowing when a custom-built solution creates a lasting advantage and when a SaaS tool is the right answer.Map current and next-state process flows across the entire internal toolchain and lead systems transformation for internal teams.Systems Architecture & EngineeringArchitect and maintain the full engineering lifecycle for internal platforms — from ideation and design through deployment, iteration, and deprecation.Build seamless, API-first ecosystems that integrate internal tools across HR systems, finance platforms, knowledge management, CRM, and developer infrastructure.Own system reliability and operational resilience: establish success metrics for uptime, performance, and employee productivity.Design scalable, secure architectures using cloud-native principles, microservices, and modern integration patterns.AI & AutomationLead the strategy for integrating AI and LLMs into internal workflows — reimagining how knowledge is shared, decisions are supported, and work is executed across the organisation.Deploy intelligent automation tools — including AI where appropriate — to streamline internal processes and improve decision-making.Evaluate and integrate AI-assisted troubleshooting, proactive recommendations, and intelligent automation into the internal platform layer.Stay ahead of technology trends and drive continuous experimentation — you build prototypes, not slide decks.Developer Experience & ProductivityReduce cognitive load for internal users by providing golden paths, standardised workflows, and self-service capabilities.Ensure frictionless onboarding and seamless integration across the tool ecosystem.Measure platform success through adoption rates, user satisfaction, DORA metrics, and productivity impact — not feature count.Team LeadershipBuild, lead, and mentor a high-performing team of engineers and engineering managers.Cultivate a collaborative engineering culture rooted in ownership, speed, and craftsmanship.Provide technical mentorship and create growth paths for individual contributors and managers alike.Foster psychological safety and a feedback-driven environment that empowers people to do their best work.Cross-Functional CollaborationPartner with People, Finance, Engineering, Legal, and Operations leadership to translate complex business needs into a unified technical vision.Serve as the bridge between business stakeholders and the engineering team — you speak both languages fluently.Align internal platform investments with broader company strategy and demonstrate measurable ROI.What You Will NeedMust-Have12+ years of experience in software engineering, with at least 5 years in engineering leadership (managing teams or managing managers).Strong hands-on technical background: you’ve built production systems and can still credibly review architecture, code, and system design.Deep understanding of cloud-based systems (AWS, GCP, or Azure), APIs, microservices, data pipelines, and modern infrastructure.Proven track record of building and scaling internal tools or platforms that serve cross-functional business teams — not just engineering.Experience making build-vs-buy decisions and managing a portfolio of custom-built and third-party tools.Strong experience designing and building internal platforms and automation systemsStrong product thinking: you define success in terms of user outcomes and business impact, not technical output.Experience navigating the full SDLC from ideation through deprecation — you know when to build, iterate, and retire.Excellent communication skills: you can articulate complex technical concepts to non-technical executives and translate business problems into engineering roadmaps.Nice-to-HaveExperience at a high-growth technology or AI-native company that scaled rapidly.Background in platform engineering, developer experience, or internal developer platforms (IDPs).Familiarity with HRIS, ERP, and business systems integration (Workday, Salesforce, NetSuite, etc.).Experience with cybersecurity best practices and compliance frameworks for internal systems.Prior experience leading internal technology through M&A integrations or multi-entity consolidation.Exposure to knowledge management systems, internal search, and enterprise AI assistants.Experience integrating AI/LLMs into internal workflows or productivity toolsWhat Success Looks LikeWithin 30 days: Completed a full audit of the existing internal toolchain, identified the top friction points, and presented a prioritised roadmap.Within 60 days: Shipped at least two high-impact internal tools or automations that measurably improve productivity, and established team operating rhythm.Within 12 months: The internal tools ecosystem is a recognised competitive advantage — teams actively request new capabilities, AI is embedded in daily workflows, and internal NPS is consistently high.Who You AreAn engineer who thinks like a CEO. You’ve built production systems, led engineering teams, and understand that the best internal tools don’t just save time — they change how an organisation thinks and moves. You’re obsessed with removing friction, allergic to manual workarounds, and energised by the idea that great internal infrastructure compounds into organisational speed. You believe internal tools deserve the same craft as customer-facing products. You see AI not as a buzzword but as the most important lever for internal productivity in a generation, and you want to be the person who pulls it.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, the process to offer may be shorter.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level automotive engineering problems grounded in real practice; Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); Improve AI reasoning to align with first principles and accepted engineering standards; Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. 3+ years of professional automotive engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $13 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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About UsAt LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.About the TeamThe Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.About the RoleThe Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.Location(s): BostonWhat You’ll DoCo-architect and co-build production AI agents with customer engineering teamsOwn the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluationsHelp customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflowsAdvise customers post-sale on architecture, best practices, and roadmap-level decisionsRun technical demos, trainings, and workshops for developer audiencesSurface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customersOccasionally contribute code upstream when it meaningfully improves customer outcomesWhat You’ll Bring3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-upStrong Python, JavaScript and systems fundamentalsHave designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handlingAre comfortable working directly with customers during POCs, architecture reviews, and technical evaluationsCan explain technical tradeoffs clearly and build trust with developer audiencesTake responsibility for outcomes, not just recommendationsHave a bias toward action and enjoy figuring things out as you goAre excited about operating AI agents in production, not just building demosNice to Have’s:You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworksWorked with LLM evaluation, observability, or guardrailsHave experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes conceptsHave shipped and operated production software and are comfortable owning systems under real-world constraintsCompensation & BenefitsWe offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.Annual OTE range: $150,000–$250,000 USD

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About the RoleWe're looking for a Solutions Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems.This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains.This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture.About Us:At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Key ResponsibilitiesInfrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelinesAgent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operationsCustomer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teamsWhat We're Looking For Required Experience7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to applyInfrastructure & Platform:3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure)Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deploymentsExperience with Infrastructure as Code (Terraform, Helm) and GitOps practicesKnowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizingExperience designing high-availability and disaster recovery solutionsStrong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog)Experience with CI/CD pipelines for infrastructure and applicationsAgent Engineering & Development:1+ years of experience building production AI/ML applications or agentsStrong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applicationsExperience with state management patterns (short-term and long-term memory)Experience designing and implementing evaluation frameworks for AI applicationsStrong prompt engineering skills with experience in optimization and A/B testingExperience with vector stores, RAG patterns, and knowledge organizationExperience with tool integration, API design, and error handling patternsStrong Python and/or TypeScript development skillsCustomer-Facing:Customer-facing experience with enterprise customersExperience conducting technical assessments or infrastructure auditsStrong communication skills with ability to explain technical concepts to diverse audiencesKey AttributesStrong problem-solving skills with ability to analyze complex requirements and design elegant solutionsExcellent customer-facing communication skills, able to explain technical concepts to diverse audiencesExperience working cross-functionally with engineering teams, product teams, and customersConsultative approach with ability to understand customer needs, provide recommendations, and guide implementationAbility to balance infrastructure architecture with agent development workStrong engineering background with hands-on development experienceLocation: Austin, TexasCompensation: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.$170K to $190K

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Research Scientist – Tabular & Structured Machine LearningThe MissionAI today is limited not only by model design but by the inefficiency of the data that feeds it. At scale, each redundant byte, poorly organized dataset, and inefficient data path slows progress and compounds into enormous cost, latency, and energy waste.Granica’s mission is to remove that inefficiency. We combine advances in information theory, probabilistic modeling, and distributed systems to design self-optimizing data infrastructure: systems that continuously improve how information is represented, compressed, and used by AI.Granica’s research group is led by Prof. Andrea Montanari (Stanford), bridging advances in learning theory and information efficiency with large-scale distributed systems. Together, we share a conviction that the next leap in AI will come not only from larger models, but from more efficient learning systems and better data representations.Most modern AI research focuses on text, images, or video. Granica’s work focuses on the far less explored but economically critical domain of large-scale structured and tabular data, which powers the majority of enterprise decision-making systems.Granica is pioneering a new class of structured AI models: foundational models built to learn and reason from relational, tabular, and structured data. While others focus on unstructured text or media, we are exploring the next frontier: systems that understand and reason over the structured information that runs the global economy.This role focuses specifically on machine learning for structured and tabular data rather than general LLM application development.What You’ll Build and ResearchInvent and prototype algorithms that advance the foundations of machine learning for structured and tabular dataDevelop new representation learning techniques and information models for large enterprise datasetsBuild adaptive learners combining statistical learning theory, probabilistic modeling, and large-scale systems optimizationContribute to the development of large tabular models and structured foundation modelsDesign architectures integrating relational, symbolic, and neural learning componentsResearch and implement methods for dataset compression, selection, and representation to improve learning efficiencyDevelop cost models and optimization frameworks for large-scale structured learning systemsCollaborate closely with the Granica research group led by Prof. Andrea Montanari (Stanford) and with systems engineersRapidly prototype new algorithms and evaluate them on real enterprise datasetsPublish and contribute to the broader research community shaping the future of structured AI and efficient ML systemsWhat You’ll BringPhD in Machine Learning, Statistics, Computer Science, Applied Mathematics, or a related fieldResearch experience related to structured, relational, or tabular dataExperience in one or more of the following areas:Tabular or relational machine learningRepresentation learning for structured dataStatistical learning theory or generalizationProbabilistic modeling or Bayesian inferenceOptimization for machine learningScalable or distributed ML systemsExperience working with structured datasets or relational data systemsStrong grounding in statistics, optimization, information theory, or probabilistic inferenceHands-on experience with PyTorch, JAX, or TensorFlowStrong programming skills in Python or RustDemonstrated ability to translate theoretical ideas into working systems or prototypesCuriosity about how structure and relational information enable new forms of learning and reasoningA pragmatic research mindset: you value elegant ideas but also ship systems that work at scaleBonusResearch in tabular machine learning, relational representation learning, or structured data modelingExperience building large-scale ML infrastructure or distributed training systemsFamiliarity with data systems, query engines, or dataset optimization pipelinesPublications at top venues such as NeurIPS, ICML, ICLR, COLT, KDD, AAAIContributions to open-source ML systems or research-to-production toolingCompensation & BenefitsCompetitive salary, meaningful equity, and substantial bonus for top performersFlexible time off plus comprehensive health coverage for you and your familySupport for research, publication, and deep technical explorationAt Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. Join us to build the foundational data systems that power the future of enterprise AI!

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Who We Are PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials.  Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes. Where You Fit  As the Associate Director, MLOps Lead, you will lead the team responsible for the backbone of our AI/ML Stack: the infrastructure that bridges ML research and massive-scale production. Your primary directive is to evolve our stack to meet the next scale of needs in large scale ML training & inference workloads.   You’re someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things better – without taking yourself too seriously. Our technical space is broad: high-scale AI training & inference workloads, cloud infrastructure, Kubernetes, observability, distributed systems, and a bit of everything in between. What You’ll Do This role is critical for driving the scalability and efficiency of our Machine Learning Operations platform with high-impact & high growth strategic initiatives.  Vision and Roadmap: Develop and execute the long term vision & roadmap for MLOPs team to support ML development and deployment needs across the business units. Successfully manage the tension between short-term tactical deliveries and long-term architectural transformation for future growth.  Team Management: Lead and mentor a team of 6-7+ high-performing engineers. Strategically allocate resources to manage support for existing services while executing key strategic initiatives. Cross-Functional Collaboration: Partner with leaders across machine learning, data science, product engineering, and infrastructure to proactively identify pain points, address bottlenecks, and facilitate the deployment of new solutions. Foundation Model Readiness: Architect the compute and storage pipelines required for ML Engineers to manage millions of slides and complex derived artifacts without data fragmentation or synchronization latency. Inference Modernization: Modernize the AI Product inference stack to support 5-10x growth of AI runs across global deployments. System Observability: Collaborate with Site Reliability Engineering (SRE) to establish comprehensive metrics covering compute under-utilization, network bottlenecks, and granular cost and turn-around-time attribution. Technology Refresh: Conduct "Build vs. Buy" assessments, leading "Stack Refresh" audits to benchmark our proprietary tools against best-in-class commercial and open-source alternatives to meet our future needs. What You Bring To be successful in this role with us, you'll at least need: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience). 2-3+ years of experience managing engineering team(s), with a focus on building production-grade frameworks for MLOps or ML Infrastructure. Deep technical expertise with ML workloads on kubernetes, cloud computing platforms (AWS/GCP/Azure), workflow orchestration (Airflow, Kubeflow, or proprietary equivalents) and DevOps principles and infrastructure-as-code (Helm, Terraform). Proven experience managing petabyte-scale datasets and high-throughput production inference pipelines. Strong software engineering skills in complex, multi-language systems and experience with scalable service architecture. Use of AI assistants (e.g. CoPilot, Cursor, Claude) across platform development lifecycle. It Would Be Great If You Also Have Exposure to ML frameworks like PyTorch or Scikit-learn. Experience with large-scale data processing frameworks (e.g. Spark, Hive, Databricks, Amazon EMR) Expertise in MLOps principles, including model lifecycle management, feature stores, model monitoring, and CI/CD for ML. Familiarity with security and compliance best practices in ML systems. We Want To Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for.  PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way. The cash compensation outlined below includes base salary or hourly wage and on-target commission for employees in eligible roles. The summary below indicates if an employee in this position is eligible for annual bonus, overtime pay and equity awards. Individual compensation packages are tailored based on skills, experience, qualifications, and other job-related factors.  Annual Pay Range: AD, MLOps: $181,500 - $278,300 Not Overtime Eligible Eligible for Equity

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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 an Engineering Manager to lead the design and implementation of Deepgram’s internal data and ML training systems. You will lead a team of engineers in building crucial components for driving a data flywheel that powers fundamental product quality as well as a system for large-scale, distributed ML training on a HPC cluster. Your ability to partner effectively with leaders and ICs in Research and DataOps while leading talented engineers to build, maintain, and extend mission-critical systems will contribute significantly to Deepgram’s competitive advantage. You will be a critical voice in Deepgram’s DataOps, Research, and Engineering teams, driving high impact products from start to finish.What You’ll DoRecruit, hire, train, and support top engineering talent to build a world-class teamTransform cross-functional visions into detailed project plans, ensuring clarity across teams on commitments, risks, and timelinesDefine and own the technical strategy enabling acceleration of Deepgram’s ML training pipelinesPromote a robust team engineering culture, including a focus on rigorous engineering standards as well as continuous improvement on team practices and processesPartner with DataOps and Research to design and implement new services, features, and/or products end to endCoach and mentor engineers to achieve high personal growth while delivering on ambitious team goalsYou’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 workSee management as an opportunity to empower a team to solve big problems through your own grit, learning, and empathyIt’s Important To Us That You HaveProven experience managing and leading and growing a team with a consistent record of mentoring and coaching team membersA strong technical background building world class solutionsThe ability to drive technical decisions in a scalable and thoughtful mannerPassion about good engineering practices, emerging technologies, and improving processesA passion for navigating the team through the real-world constraints of a startup: how to build quickly, iterate frequently, and run experimentsStrong practical experience with software architecture and implementation, plus the ability to engage with an Engineering team to help build and scale the existing infrastructureIt Would Be Great if You HadExperience working in high-growth startupsFamiliarity with hybrid cloud models (bare-metal datacenters and cloud service providers) and scaled databasesDeep experience with machine learning training, inference, or bothBenefits & 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 HappyRobotHappyRobot is the AI-native operating system for the real economy—a system that closes the circuit between intelligence and action. By combining real-time truth, specialized AI workers, and an orchestrating intelligence, we help enterprises run complex, mission-critical operations with true autonomyOur AI OS compounds knowledge, optimizes at every level, and evolves over time. We’re starting with supply chain and industrial-scale operations, where resilience, speed, and continuous improvement matter most—freeing humans to focus on strategy, creativity, and other high-value tasks. You can learn more about our vision in our Manifesto. HappyRobot has raised $62M to date, including our most recent $44M Series B in September 2025. Our investors include Y Combinator (YC), Andreessen Horowitz (a16z), and Base10—partners who believe in our mission to redefine how enterprises operate. We’re channeling this investment into building a world-class team: people with relentless drive, sharp problem-solving skills, and the passion to push limits in a fast-paced, high-intensity environment. If this resonates, you belong at HappyRobot.Role OverviewWe are looking for a versatile and highly skilled Forward Deployed Engineer to join our team. In this role, you will combine strong technical abilities with excellent communication skills, working directly with customers to ensure they maximize the value of HappyRobot’s AI platform. You will be involved in onboarding, implementation, and ongoing support, while also contributing to product development and innovation.What You’ll DoCustomer-Facing Engineering – Work closely with customers from onboarding to ongoing usage, helping them integrate and optimize our AI solutions.Technical Development – Build new features, MVPs, and scalable solutions that directly impact customer outcomes.Full-Stack Development – Utilize React, TypeScript, Node.js, and Python to develop robust applications and tools.AI/ML Applications – Design, implement, and iterate on AI/ML solutions, including LLM prompting, tuning of voices, and transcribers to optimize use cases.Integration & APIs – Manage APIs and integrations with third-party systems to ensure seamless functionality for customers.Cross-Functional Collaboration – Partner with Product, Engineering, and Customer Success teams to deliver tailored solutions.Iterative Problem-Solving – Continuously iterate and improve AI solutions based on customer feedback and evolving requirements.Project Management – Prioritize and manage multiple projects under tight deadlines while maintaining high-quality results.Must HaveStrong full-stack experience: React, TypeScript, Node.js.Hands-on proficiency in Python.Experience building AI/ML applications, including LLM prompting and tuning.Ability to manage APIs and integrate with third-party systems.Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.Proven ability to prioritize and manage multiple projects under tight deadlines.Founder mindset: highly independent, takes ownership, and thrives in a fast-paced environment.Why join us?Opportunity to work at a high-growth AI startup, backed by top investors.Rapidly growing and backed by top investors including a16z, Y Combinator, and Base10.Ownership & Autonomy - Take full ownership of projects and ship fast.Top-Tier Compensation - Competitive salary + equity in a high-growth startup.Work With the Best - Join a world-class team of engineers and buildersOur Operating Principles Extreme OwnershipWe take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting — if something needs fixing, we own it and make it better. This means stepping up, even when it’s not “your job.” If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don’t wait for someone else to solve it — we lead with accountability and expect the same from those around us.CraftsmanshipPutting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for “just fine.” We sweat the details because details compound. Whether it’s a product feature, an internal doc, or a sales call — we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build — even when nobody’s watching.We are “majos” Be friendly & have fun with your coworkers. Always be genuine & honest, but kind. “Majo” is our way of saying: be a good human. Be approachable, helpful, and warm. We’re building something ambitious, and it’s easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego.Urgency with Focus Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We’re running a high-speed marathon — not a sprint with no strategy.Talent Density and Meritocracy Hire only people who can raise the average; ‘exceptional performance is the passing grade.’ Ability trumps seniority. We believe the best teams are built on talent density — every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players — that’s how we win.First-Principles Thinking Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don’t copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It’s how we build what others think is impossible.The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller.By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer.In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data.If you wish to exercise your rights of access, rectification, deletion, portability, or opposition in relation to your personal data, you can do so through security@happyrobot.ai, subject to the GDPR.For more information, visit https://www.happyrobot.ai/privacy-policyBy submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!About the role.We’re building the next generation of agentic AI infrastructure at Cohere. This team sits at the intersection of ML systems, distributed infrastructure, and developer experience, creating the platform that powers autonomous AI agents at scale.You’ll work on hard, forward-looking problems with few established patterns, including secure code execution, agent state management, model routing, identity and authentication, and resource management for long-running agent workflows.This role is a strong fit for someone who combines systems depth with ML intuition. You should be comfortable building reliable infrastructure, thinking through distributed systems tradeoffs, and understanding how emerging agentic capabilities shape platform design.What you’ll work on.Secure execution environments for agent-generated codeIdentity, authentication, and trust boundaries for agentsModel routing and orchestration across different model types and environmentsRate limiting, quotas, and resource management for agent workflowsState management, memory, and filesystem abstractions for agents. In this role you will:Turn emerging ML research ideas into production-ready infrastructureBuild core platform capabilities for execution, storage, and state managementPrototype and evaluate new technologies, then help decide what should move into productionPartner with research teams to shape infrastructure based on what future agent systems will needYou may be a good fit if you have:Experience building production ML infrastructure with strong systems fundamentalsHands-on work with agentic systems, multi-agent workflows, or agent development frameworksFamiliarity with model routing and LLM provider frameworks across different model types and environmentsExperience with scalable, fault-tolerant distributed systems and KubernetesA track record of moving quickly on prototypes and making good decisions about productionization. BonusExperience across on-prem, private cloud, and public cloud environmentsFamiliarity with storage systems, embedded databases, or filesystem abstractionsExperience with code execution sandboxes such as gVisor, Firecracker, Kata, or WASM runtimesInterest in emerging ML infrastructure, edge inference, or browser-native modelsOpen-source contributions to LLM or agent infrastructure projectsExperience with identity, workload auth, or capability-based security systems.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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Role Overview Scale’s rapidly growing International Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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About UsAt LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.About the TeamThe Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.About the RoleThe Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.Location: AtlantaWhat You’ll DoCo-architect and co-build production AI agents with customer engineering teamsOwn the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluationsHelp customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflowsAdvise customers post-sale on architecture, best practices, and roadmap-level decisionsRun technical demos, trainings, and workshops for developer audiencesSurface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customersOccasionally contribute code upstream when it meaningfully improves customer outcomesWhat You’ll Bring3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-upStrong Python, JavaScript and systems fundamentalsHave designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handlingAre comfortable working directly with customers during POCs, architecture reviews, and technical evaluationsCan explain technical tradeoffs clearly and build trust with developer audiencesTake responsibility for outcomes, not just recommendationsHave a bias toward action and enjoy figuring things out as you goAre excited about operating AI agents in production, not just building demosNice to Have’s:You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworksWorked with LLM evaluation, observability, or guardrailsHave experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes conceptsHave shipped and operated production software and are comfortable owning systems under real-world constraintsCompensation & BenefitsWe offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.Annual OTE range: $150,000–$250,000 USD

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level automotive engineering problems grounded in real practice; Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); Improve AI reasoning to align with first principles and accepted engineering standards; Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. 3+ years of professional automotive engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level automotive engineering problems grounded in real practice; Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); Improve AI reasoning to align with first principles and accepted engineering standards; Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. 3+ years of professional automotive engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Founded in 2016 with offices in Los Angeles, New York, and San Francisco, M13 is an early-stage (seed and Series A) venture capital firm that invests in visionary founders building disruptive software businesses. We are a full-stack partner with a deep bench of full-time operators to help you scale efficiently and build category-defining companies.We’re seeking an Investment Summer Associate to join M13 for the summer at our San Francisco office and work directly with M13’s Investment Team on building AI-native internal tools that enhance how we source, diligence, and invest in companies.This internship blends product building, venture capital exposure, and founder engagement. In addition to company diligence and research, you will design and build a proprietary sourcing tool that helps the Investment Team identify high-potential founders and companies faster and more intelligently.You won’t be working on a theoretical project; your work will result in a real, functional product the investment team uses daily.This internship is ideal for rising undergraduate seniors, or current graduate students.What You’ll Be DoingDesign and build a proprietary AI-powered sourcing tool for the Investment TeamWork cross-functionally with investors to understand sourcing workflows and pain pointsAttend founder events, hacker house demo days, accelerators, and technical meetups to identify emerging buildersConduct calls with founders and support active deal diligenceContribute research that informs ongoing investment thesis developmentServe as a thoughtful and professional ambassador for M13 within technical communitiesThis role blends technical product building with real-time exposure to venture investing.Key DeliverablesThe Investment Team is constantly evaluating new founders, emerging technologies, and frontier AI companies. However, much of the sourcing and evaluation workflow remains manual and fragmented.This internship focuses on building a proprietary internal sourcing tool that leverages AI and automation to improve how we identify promising founders and companies and surface relevant signals across ecosystems. Your objective is to:Build a sourcing tool that meaningfully improves how the team identifies and evaluates opportunitiesDevelop structured documentation for tool handoff and iterationWhat You’ll GainDirect exposure to sourcing, diligence, and early-stage investment decision-makingInsight into how investment theses translate into pipeline-buildingHands-on experience building products within a venture firmReal-world application of AI tools in a business-critical environmentExperience collaborating across investment and platform teamsWhat You’ll Bring to the InternshipCurrently enrolled as a full-time rising undergraduate senior or graduate studentAble to work from our San Francisco office from Monday, June 15 - Friday, August 14, 2026Strong interest in venture capital, startups, and emerging AI technologyTechnically minded: this can mean you have a CS background, vibe code in your spare time, or have experience working in product or software engineeringProduct-minded thinking and ability to translate ambiguous workflows into usable softwareAbility to independently drive a project from concept through executionComfort engaging with technical founders and participating in founder communitiesFamiliarity with AI-native development tools (e.g., Cursor, Claude Code, Loveable, Riplet, or similar tools)Strong networks in the San Francisco Bay AreaCuriosity, ownership, and a low-ego, team-oriented mindset Research shows that while men apply to jobs when they meet an average of 60% of the criteria, women and other underrepresented individuals tend to apply only when they meet every requirement. If you’re excited about this role but don’t meet every qualification, we still encourage you to apply — we’d love to hear from you.M13 provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or expression. We value diverse perspectives and encourage candidates from underrepresented backgrounds to apply.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level automotive engineering problems grounded in real practice; Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); Improve AI reasoning to align with first principles and accepted engineering standards; Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. 3+ years of professional automotive engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $40 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Intrinsic is Alphabet’s bet aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.  Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.Role As a Senior AI Research Scientist for Perception for Contact Rich Manipulation you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. How your work moves the mission forward Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap. Skills you will need to be successful PhD in Computer Science, Robotics, or a related field with a focus on machine learning or computer vision. 3 years of experience in applied research focused on robotic manipulation or robot learning. Proficiency in programming with Python and C++. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Experience developing algorithms for vision-based manipulation or contact-rich interaction. Publication record in top-tier robotics or AI conferences (e.g., ICRA, IROS, CVPR, NeurIPS).  Skills that will differentiate your candidacy Experience with reinforcement learning or imitation learning for robotics. Familiarity with physics simulators like MuJoCo, Isaac Sim, or Gazebo. Experience integrating tactile sensors with visual perception systems. Experience in LfD (Learning from Demonstrations), kinesthetic learning. Background in sim-to-real transfer techniques for manipulation policies. Experience with transformer-based architectures or foundation models in a robotics context. Experience deploying machine learning models on edge compute hardwar​e. At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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Please submit your CV in English and indicate your level of English proficiency.Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.About the RoleThis project is suited for a Senior Python developer with deep functional testing experience, strong Linux and Docker skills, the ability to read code across multiple languages with the support of LLMs (e.g., C, Rust, Go) and translate requirements for migration tasks, and confidence using tools like Roo Code or Claude Code to accelerate iterative development.Key ResponsibilitiesCreate functional black box tests for large codebases in various source languagesCreate and manage Docker environments to ensure 100% reproducible builds and test execution across different platformsMonitor code coverage and configure automated scoring criteria to meet industry benchmark-level standardsLeverage LLMs (Roo Code, Claude) to accelerate development cycles, automate repetitive tasks, and improve overall code qualityRequirements5+ years of experience as a Software Engineer (primarily Python)Deep experience with pytest (fixtures, session-scoped, timeouts) and designing black-box functional tests for CLI toolsExpert-level Docker skills (reproducible Dockerfiles, user contexts, secure workspaces)Strong Linux & Bash scripting skills and comfort debugging inside containersProficiency with modern Python tooling (uv, pyproject.toml, packaging)Ability to read and understand with LLM many coding languages (for example C, C++, Rust, or Go) Experience using LLMs (Claude Code, Roo Code, Cursor) to accelerate iterative development and test-case generationEnglish language - B2 or higherRequirements +Prior experience with agent evaluation platforms and MCP CLITools and Technologies: Python (pytest, uv, Pillow), Docker, Bash, Git Submodules, C/C++/Rust/Go (reading), Dagger, GitHub Codespaces, LLMs (Claude Code, Roo Code, Cursor), coverage.py, gcov, kcov.BenefitsWhat we can offerFreelance project-based collaboration via the Mindrift platform (powered by Toloka AI)Fully remote and flexible participation — choose when and how much to contribute (20-30 hours per week)Each project has its own compensation level based on scope and expertise required. On this project, AI trainers earn up to $50 per hour equivalent.Opportunity to contribute to innovative AI projects for leading tech companiesSupportive global community