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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 Norm AiNorm Ai, the leading Legal & Compliance AI company, has a client base with a combined $30 trillion in assets under management. By turning legal code into AI code, Norm enables enterprises to move faster and more comprehensively in their legal and compliance processes with reliability and trust.Norm’s platform combines frontier AI, proprietary legal reasoning systems, and embedded legal and regulatory expertise.We have recently raised more than $140 million, backed by Blackstone, Bain Capital, Vanguard, Citi, New York Life, TIAA, Coatue, Craft Ventures, Henry R. Kravis (KKR co-founder), and Marc Benioff (Salesforce CEO).Norm Ai pioneered Legal Engineering, the process that empowers lawyers to build and supervise domain-specific AI agents with Norm’s proprietary suite of no-code software tools. We hired dozens of lawyers from premier U.S. law firms and trained them as Legal Engineers, who specialize in Large Language Model powered legal workflows.Norm Ai technology is deployed inside many of the largest and most consequential institutions in the world. The company is growing quickly and hiring across all teams. AI Fluency: Norm Ai expects all team members to be fluent in AI. Successful candidates actively use AI in their day-to-day work to support thinking, creation, and problem-solving. They use it to improve the quality and speed of their work and to continuously refine how work gets done end-to-end. Candidates should be prepared to demonstrate and discuss their AI usage throughout the interview process, including concrete examples of tools, workflows, and outcomes. We look for practical, hands-on experience, not theoretical familiarity.About Norm LawNorm Law is the first AI-native full-service law firm for global institutional clients like Blackstone (see recent coverage of our Blackstone partnership here). Legal Engineering, a discipline pioneered by Norm Ai, where lawyers develop legal AI agents, powers Norm Law to deliver faster, more precise, and more consistent legal services. With purpose-built AI agents completing first passes of work, Norm lawyers supervise, review, and focus on what matters most: strategic judgment and expert advice.Norm Law and Norm Ai, together, are building Legal AGI.This RoleAs a Senior Data Scientist at Norm, you will join our growing data team to build and scale our analytics capabilities. You'll develop data models and insights that power our AI compliance engine and shape how we measure, understand, and optimize our product. Working directly with our Director of Data and cross-functional partners in Product, Engineering, and Executive teams, you will translate complex Compliance and Legal Engineering workflows into actionable insights while helping establish best practices and foundations for our expanding analytics function.You Will:Design and maintain multi-dimensional measurement frameworks for evaluating AI performance across the Norm Law workflowAnalyze telemetry and behavioral logs to understand how attorneys, legal engineers, and clients interact with AI-generated work, surfacing drivers of quality and efficiencyDesign and run experiments with rigorous statistical design, clear hypotheses, and honest accounting of real-world constraintsDevelop frameworks to measure and communicate performance across key dimensions of legal work qualityImplement product analytics to understand how enterprise clients engage with our AI-driven compliance and legal workflowsBuild self-service analytics capabilities so legal engineers and business stakeholders can monitor performance independentlyBuild data models; contributing to ELTprocesses using dbt, Airflow, and our cloud data warehouseHelp establish data governance practices that meet enterprise security and regulatory compliance requirementsSkills & Experience - Core5-7 years of data science experience with demonstrable statistical depth1-2 years of data engineering exposureData Science experience and strong experimental design skills such as hypothesis testing, A/B testingExperience defining and measuring quality in ambiguous, multi-dimensional settingsProficiency with SQL, Python, and modern data stack tools (dbt, Hex, Airflow, Snowflake/BigQuery/Redshift)Strong analytical background with experience at small startups where you've worn multiple data hatsExperience building analytics from scratch at early-stage companiesB2B SaaS experience with understanding of enterprise customer analyticsAbility to translate complex business questions into technical data solutionsSkills & Experience - PlusesExperience with AI/ML model evaluation: precision/recall trade-offs, calibration, distribution shift, behavioral monitoringExperience working with sparse labels or human-in-the-loop evaluation set upsAnalytics experience in regulated industries (FinTech, RegTech, compliance)Background working with enterprise compliance or legal workflowsStartup experience with rapidly changing analytics requirementsWhat Success Looks Like - 30 DaysDevelop comprehensive understanding of our product and current data landscapeAssist in setting up foundational data infrastructure and begin implementing core analytics trackingDocument our data requirements and create a roadmap for analytics capabilitiesEstablish relationships with key stakeholders across Product, Engineering, and Business teamsWhat Success Looks Like - 60 DaysDeploy production data pipelines and establish reliable data collection across the platformLaunch initial set of product analytics dashboards for user behavior and AI model performanceBegin analysis of compliance workflow patterns to identify optimization opportunitiesCreate self-service analytics capabilities for the broader teamCompensation and Benefits$175,000 - $215,000 annuallyThe range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills (as uncovered during the interview process), experience, and relevant education or training. Please note that the compensation details listed here reflect the base salary only, and do not include equity or benefits. We offer a competitive salary along with equity compensation. Our comprehensive benefits package includes a 401(k) plan with an employer match. Employees enjoy top-tier insurance coverage, encompassing health, dental, hospital, accident, and vision plans. For candidates needing to relocate to NYC, we provide relocation reimbursement. You'll thrive in our fast-paced learning environment where professional growth is constant.We embrace a hybrid model, typically in-office 3-4 days per week.To learn more about Norm Ai, visit our website.

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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 intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $58 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.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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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 $12 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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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.Opportunity:Deepgram is looking for a Backend Software Engineer to join the Engine team to lead the design and implementation of Deepgram’s products. You will design and implement secure, robust, and scalable services for speech processing; efficient, distributed compute orchestration; optimized scheduling, and more. Your skill at building highly reusable code that overcomes technical challenges is paired with an intuition for delightful user experiences. You will be a critical voice in Deepgram’s Product and Engineering teams, driving high impact products from start to finish.What You’ll DoImprove Deepgram’s core inference services including areas in networking, speech processing, audio transcoding, and latency and memory optimizationDevelop processes for measuring, building, and optimizing services to maximize system performanceDebug complex system issues that include networking, scheduling, and high performance computing interactionsRapidly customize backend services to support our customer needsPartner with Product to design and implement new services, features, and/or products end to endYou’ll Love This Role If YouThrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessityEnjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design workIt’s Important To Us That You Have3+ years of experience in an industry roleProgramming experience in Rust (or C, C++), with competence in PythonExcellent communication and organizational skills, both written and verbal.A high level of experience and understanding of version control; preferably git.Comprehensive experience with UNIX-style systems.It Would Be Great if You HadExperience with modern machine learning, such as experience with a framework like Torch or implementation knowledge of architectures like CNNs, RNNS, and transformersExperience with audio processingBenefits & Perks*Holistic healthMedical, dental, vision benefitsAnnual wellness stipendMental health supportLife, STD, LTD Income Insurance PlansWork/life blendUnlimited PTOGenerous paid parental leaveFlexible schedule12 Paid US company holidaysQuarterly personal productivity stipendOne-time stipend for home office upgrades401(k) plan with company matchTax Savings ProgramsContinuous learningLearning / Education stipendParticipation in talks and conferencesEmployee Resource GroupsAI enablement workshops / sessions*For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible.Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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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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About the TeamThe AI Deployment Engineering team works at the intersection of cutting-edge AI research and real-world application. We partner directly with OpenAI’s most strategic customers to design, implement, and scale production deployments of generative AI systems. Our work ensures that organizations can safely and effectively integrate AI into critical workflows.Within this team, the Health & Life Sciences (HLS) segment focuses on enabling pharmaceutical manufacturers, biotechnology companies, medical device organizations, contract research organizations (CROs), and health systems to adopt AI responsibly in regulated environments. We work across clinical, scientific, regulatory, and operational functions to unlock meaningful impact while maintaining the highest standards of safety, privacy, and compliance.About the RoleWe are seeking a Manager, AI Deployment Engineering to lead our Healthcare & Life Sciences deployment efforts. In this role, you will build and mentor a high-performing team of deployment engineers dedicated to helping HLS organizations move from experimentation to production with OpenAI technologies.You will operate at both strategic and technical levels — partnering with executive stakeholders, technical leaders, and cross-functional internal teams to deliver secure, compliant, and high-impact AI deployments. This role requires a strong technical foundation, people leadership experience, and a deep appreciation for the complexity of regulated healthcare and life sciences environments.This role is based in San Francisco or Seattle. We use a hybrid work model of 3 days in the office per week.In this role, you will:Own the strategy and operating model of the HLS AI Deployment Engineering team, ensuring alignment with company objectives and the evolving needs of our customers.Hire, mentor, and develop a high-impact team of AI Deployment Engineers focused on HLS production deploymentsEstablish operating mechanisms, delivery standards, and best practices tailored to regulated environmentsFoster a culture of technical excellence, customer empathy, and responsible AI deploymentDrive Successful Enterprise Deployments and oversee end-to-end implementation of generative AI applications in production across healthcare and life sciences organizationsGuide customers through complex integration efforts spanning R&D, clinical development, regulatory affairs, medical affairs, and ITDevelop scalable frameworks for secure, compliant AI adoption in environments governed by HIPAA, GxP, FDA, EMA, and related regulatory standardsEnsure measurable impact through activation, adoption, and workflow transformation (e.g., drug discovery acceleration, clinical documentation support, regulatory submission drafting)Collaborate closely with Sales, Account Directors, Solutions Architects, Product, Security, and Legal teamsServe as a trusted technical advisor to executive and senior technical stakeholders at enterprise HLS customersProvide structured product feedback informed by real-world deployment challenges and industry requirementsYou’ll thrive in this role if you:Have 8+ years of experience in technical delivery, solutions engineering, or deployment roles, including people management experienceHave led enterprise-scale implementations of AI, ML, or platform technologiesBring experience in healthcare or life sciences environments, including familiarity with clinical research, drug development, regulatory operations, or health system infrastructureUnderstand compliance frameworks such as HIPAA, GxP, and global regulatory considerationsAre comfortable engaging with executive stakeholders while maintaining technical depthEnjoy operating in ambiguous, fast-moving environments and building structure where it does not yet existCare deeply about responsible AI and its application in high-stakes domainsAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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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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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 intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. 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.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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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 rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) 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 $50 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 $35 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 $33 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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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 intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $58 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.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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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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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 $38 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 rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) 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 $50 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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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!