Ai Research Scientist Jobs

We at NVIDIA seek an Senior Developer Relations, Automated Synthetic Chemistry Science Lead who can coordinate science streams. This role exists at the crossroads of experimental science, optimization, analytical characterization, AI modeling, laboratory automation, and data infrastructure. It demands a practitioner with a background in research who can lead interdisciplinary science teams and accelerate experimentation without compromising scientific quality. What you'll be doing: Coordinate the operating plan across research priorities, technical execution, and program achievements. Convert research objectives into experimental priorities, parameter-space development, campaign planning, and success criteria. Lead research initiatives encompassing synthetic chemistry, catalysis, process chemistry, machine learning, automated systems, and data processing. Build standardized experimental traces capturing successful and unsuccessful outcomes, metadata, quality-control signals, analytical summaries. Guide AI systems for feasibility assessment, outcome prediction, optimization, scope exploration, and campaign orchestration. Integrate automated experimentation, analytical data streams, data curation, model retraining, and campaign decisions into a closed-loop operating model. Establish science-stream governance: build reviews, decision logs, risk and dependency tracking, quality thresholds, and paths for addressing blocking issues. Prepare recurring workstream readouts for program leadership, including scientific progress, critical decisions, cross-team dependencies, resource needs, and unresolved risks. What we need to see: PhD (or equivalent experience) with 10+ years of hands-on experience in experimental science, chemical engineering, material science, robotics, a

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description Gilead Sciences, Inc. is a research-based biopharmaceutical company that discovers, develops and commercialises innovative medicines in areas of unmet medical need. With each new discovery and investigational drug candidate, we seek to improve the care of patients living with life-threatening diseases around the world. Gilead’s therapeutic areas of focus include HIV/AIDS, liver diseases, cancer, inflammation and serious respiratory conditions. For more information please visit Gilead.com An exciting opportunity has arisen within the Global Decision Sciences & Insights team for a Director, Integrated Insights for Liver & Inflammation Pipeline. Inflammation/ Liver is

Responsibilities: Annotate Case Report Form (acrf.pdf) following FDA/CDISC or sponsor guidelines. Develop SDTM specifications and generate SDTM datasets using SAS. Develop ADaM specifications and generate ADaM datasets using SAS based on Statistical Analysis Plan. Develop Tables, Listings, Graphs, Patient Profile in support of the Clinical Study Report, Posters, Manuscripts. Develop ADaM data, Tables, Listings, Figures for Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE). Create electronic submission package to FDA, e.g., define.xml or define.pdf following FDA guidelines with minimum supervision. Proficient in analyze information and develop innovative solutions to programming and data analysis challenges; Support the point of contact (POC) of programming with statisticians for statistical input and analysis interpretation Follow and reinforce regulatory agency requirements during daily job. Serve as a programming team lead and contribute to department initiative. Provide guidance, mentoring, training for team members and help solve issues from cross-functional teams. Review draft and final production deliverables for project to ensure quality and consistency. Skills and Qualifications: Bachelor’s/Master’s degree in Statistics, Mathematics, Computer Science, Electrical Engineering, Biotechnology or related scientific disciplines with at least 4+ years of clinical programming experience. Proven knowledge and training in high level computing languages such as. SAS, C/C++, Java, R, Python, MATLAB and SQL. Database programming experience is a plus. Proficient in decoding programming logic and assembling programming code based on logic provided and be able to explain to team members. Proficient in applying concepts in Artificial Intelligence and Machine Learning in the real world. In-depth knowledge of ICH, Good Clinical Practices, Clinical research, Clinical trial process and related regulatory requirements and terminology. Good understa

About the team OpenAI’s Forward Deployed Engineering (FDE) team partners with global pharma and biotech, CROs, and research institutions to deploy production-grade AI systems across the R&D value chain. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments. About the role As a Life Sciences FDE Manager, you’ll lead a team of FDEs delivering production AI systems across drug discovery and development workflows. You’ll own delivery outcomes and team leverage while staying hands-on as a player-coach. This includes building and shipping alongside the team, setting technical direction, and maintaining a high bar for production-grade systems in regulated environments. We measure success through the health and quality of your FDE team, production adoption and measurable workflow impact, the quality of eval-driven feedback delivered back to Product and Research, and the repeatability of deployment patterns across life sciences customers. This role is based in New York City We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. This role will require travel up to 25%. In this role you will Lead and grow a team of FDEs delivering production AI systems across regulated life sciences environments Be accountable for your team’s end-to-end delivery outcomes, balancing scope, speed, robustness, and risk in high-stakes deployments Coach and develop engineers through direct feedback, high technical standards, and clear expectations for execution and ownership Operate as a player-coach, directly contributing to production systems while leading, coaching, and setting technical direction Guide teams through ambiguous, multi-workstream engagements spanning data, workflows, infrastructure, security, and scientific stakeholders Run evaluation loops that measure model and system quality against

The role will involve contributing to the development and enhancement of the credit risk modelling toolkit while partnering with modellers to ensure the toolkit is being used correctly and efficiently; and gather feedback to support future improvements and enhancements. This position requires strong stakeholder engagement skills, the ability to understand end-user requirements, and solid Python development experience, including contributing to large-scale Python libraries and testing frameworks. Essential Skills Strong commercial experience building and testing Python applications in a professional environment. Strong understanding of object-oriented programming and test-driven development. Solid knowledge of testing principles and best practices, including experience with pytest. Strong understanding of coding best practices and writing clean, maintainable, pythonic code. Experience identifying and addressing code smells. Familiarity with code review best practices. Practical understanding of SOLID principles and common design patterns. Good working knowledge of Git version control. Experience working in Agile development environments, ideally with continuous integration practices. Nice to Have MSc or PhD in Computer Science, Mathematics, Physics, Operational Research, Information Systems, or a related technical discipline. Exposure to credit risk analytics or related financial risk domains. Strong familiarity with the scientific Python stack, including NumPy, SciPy, pandas, polars, and Matplotlib. Experience with PySpark or other Big Data technologies. Experience contributing to open-source projects or developing reusable Python libraries. How to apply: Apply via the form below and tell us a bit about you. Complete the online assessment (we’ll send you a link by email). Complete the interviews with our friendly talent team over phone and video. Lastly, you’ll interview with one or more of our clients. So you don’t miss out on your dream job, we encourage you

Responsibilities: Annotate Case Report Form (acrf.pdf) following FDA/CDISC or sponsor guidelines. Develop SDTM specifications and generate SDTM datasets using SAS; Develop ADaM,specifications and generate ADaM datasets using SAS based on Statistical Analysis Plan; Develop Tables, Listings, Graphs, Patient Profile in support of the Clinical Study Report, Posters, Manuscripts; Develop ADaM data, Tables, Listings, Figures for Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE) Create electronic submission packages to FDA, e.g., define.xml or define.pdf following FDA guidelines with no supervision. Expert-level in analyze information and develop innovative solutions to programming and data analysis challenges; Serve as point of contact (POC) of programming with statisticians for statistical input and analysis interpretation; Follow and reinforce regulatory agency requirements during daily job. Serve as a programming team lead and contribute to department initiatives. Provide guidance, mentoring, training for team members and help solve issues from cross-functional teams; Review draft and final production deliverables for project to ensure quality and consistency. Work with global team or sponsors to coordinate project deliverables, timelines and resources. Skills and Responsibilities: Bachelor’s/Master’s degree in Statistics, Mathematics, Computer Science, Electrical Engineering, Biotechnology or related scientific disciplines with 5+years of clinical programming experience. Proven knowledge and training in high level computing languages such as. SAS, C/C++, Java, R, Python, MATLAB and SQL. Database programming experience is a plus. Expert-level in decoding programming logic and assembling programming code based on logic provided and be able to explain to team members. Expert level in applying concept in Artificial Intelligence and Machine Learning in real world. In-depth knowledge of ICH, Good Clinical Practices, Clinical research, Clinical tria

About Graphcore At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. Job Summary As a research engineer at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. We are therefore looking for individuals who combine strong machine learning experience with practical engineering skills to deliver impactful AI research. We are seeking AI researchers with strong software engineering experience, particularly in lower-level programming and performance optimisation for hardware efficiency. Our research spans a broad range of topics, including efficient training and inference, world models, life sciences, reinforcement learning, and beyond. You will work closely with researchers to generate ideas and translate them into scalable implementations, contributing to publications and projects that help to steer the future of AI hardware. The Team Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence a

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

Our team is seeking to extend the internship of our current AI Research Intern for the TAO (Train, Adapt, Optimize) Multi-Modal Model Development project, recognizing their exceptional performance and strong alignment with the team’s research goals. Their innovative ideas and technical contributions have significantly enhanced our work. Given the rapidly evolving field of multi-modal AI, encompassing vision-language modeling, universal segmentation, and large-scale model training, extending this internship will provide further growth opportunities for the intern while strengthening our team’s capacity to develop scalable, high-impact AI solutions. Embark on an exciting journey with NVIDIA, a global leader in AI and accelerated computing. As an AI Research Intern focusing on multi-modal AI and vision-language model development within the TAO framework in Hanoi/HCM City, Vietnam, you will be at the forefront of advancing cutting-edge machine learning research. You’ll collaborate with a talented team of engineers and researchers dedicated to developing state-of-the-art deep learning models for tasks such as image segmentation, cross-modal understanding, and universal representation learning. This internship offers a unique opportunity to contribute to next-generation AI systems with real-world impact across industries—from autonomous vehicles to intelligent content understanding. What you'll be doing: Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks. Contribute to the design and implementation of vision-language models (VLMs) and universal segmentation systems. Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability. Collaborate with cross-functional teams to integrate your research into production-le

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

Technical Program Manager – AI Research itD is seeking a Technical Program Manager – AI Research to oversee business-critical projects in the AI Research space, facilitating review and approval processes that enable research initiatives to be initiated and shipped successfully. The ideal candidate will bring 5+ years of technical program management experience in a technology environment, including AI compliance reviews, and a track record of managing complex, cross-functional initiatives in ambiguous environments. Location: onsite presence in New York City 3 days per week. Pay Rate: $53/hr to $54/hr depends on Experience We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities Lead multiple compliance reviews for frontier AI research projects, including drafting requirements, monitoring progress, managing action items, and resolving blockers to keep milestones on schedule. Coordinate with requesters, engineering, research teams, reviewers, and privacy stakeholders to clarify requirements and streamline review and approval processes. Develop and maintain clear project communications, providing regular updates and weekly reporting on project status, accomplishments, risks, dependencies, and review-process insights. Identify project risks and dependencies early, develop mitigation plans, and escalate issues that may affect review timelines or key milestones. Research, catalog, and annotate AI Research assets with a high degree of accuracy and attention to detail. Analyze data and optimize workflows using Google Sheets and Microsoft Excel, including data exploration, annotation, and reporting. Monitor developments in AI research, compliance, and related tooling to identify opportunities for continuous process and project improvements. Internal Responsibilities Attend regular internal practice community meeting

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for talented systems developers and researchers to join the Snowflake AI Research team and advance the state of the art in LLM inference systems and optimization . Our mission is to build the next generation of high-performance and intelligent inference systems . We optimize not only how fast and efficiently models run, but also how quickly inference systems can adapt to new models, architectures, hardware, and workloads. Our work spans the full inference stack—from distributed serving and runtime systems to GPU kernels and model-system co-design. We explore techniques such as adaptive parallelism, speculative and parallel decoding, disaggregated inference, scheduling and batching, KV-cache optimization, model swapping, quantization, and GPU kernel optimization to push the frontier of latency, throughput, scalability, and cost. Beyond optimizing individual models, we are building intelligent and adaptive inference systems that can automate performance optimization—rapidly profiling new models and workloads, identifying bottlenecks, selecting effective execution strategies, and adapting system configurations with minimal manual tuning. We embrace AI-native engineering , using AI not only as the workload we optimize, but also as a tool to accelerate system deve

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. The Opportunity Adyen is building a top-tier AI engineering organization in Amsterdam, San Francisco and Madrid to drive our next chapter of innovation using AI globally across the entire company. This is a highly technical, hands-on role focused on the exploration and application of cutting-edge AI research within the financial technology sector. As a Senior AI Research Engineer, you will operate with a high degree of autonomy and responsibility , delivering strategic, high-impact outcomes that bridge the gap between advanced AI research and production-grade applications at a global scale, potentially impacting trillions of dollars in transactions annually. What You'll Do: Innovate and Deploy: Drive the execution of Adyen's AI strategy , focusing on the practical application of Generative AI (GenAI) and other AI methodologies in finance . This includes contributing to Adyen's efforts in key research areas such as AI agents for data analysis and operational workflows , human-in-the-loop for integrity risk , and development of foundation models . For instance, you might contribute to initiatives like the Data Agent Benchmark for Multi-step Reasoning (DABStep) , which evaluates AI agents on real-world data analysis tasks, including those from the financial sector. Build Production-grade Applications: Bridge the gap between cutti

About the Team AI Research Lab is one of DoorDash’s frontier innovation hubs, focused on building the foundation for an AI-native future across our three core audiences: consumers, merchants, and dashers. As AI capabilities accelerate, the AI Research Lab operates at the center of technical exploration and real-world execution — connecting frontier model research, internal platform investments, operator teams, and strategic external partners. Our mission is to translate cutting-edge AI research into scalable, production-ready systems that drive measurable business impact. We combine deep technical rigor with strong operational execution to ensure that breakthrough capabilities become durable competitive advantages for DoorDash. About the Role As an Associate Manager, Strategy & Operations on our AI Research Lab, you will play a central role in converting frontier AI advancements into shipped products and scalable infrastructure. You will operate across research, product, and operations to move from early discovery and experimentation to deployment and impact. This role sits at the intersection of customer insight, technical innovation, and business execution. You will help define and scale the Lab’s most important bets while building the foundations that enable AI applications to compound over time. You’re Excited About This Opportunity Because You Will … Reimagining core experiences through AI, such as the merchant journey, by partnering directly with in-field merchants, sales, support, product, and engineering teams. You will help unify major initiatives into a coherent, AI-native interaction model. Own revenue-driving AI initiatives, operating as the accountable business owner for high-priority AI bets and ensuring clear linkage between technical progress and financial outcomes. Lead business planning cycles, developing go-to-market strategies for AI-powered products and capabilities, overseeing execution through structured project plans, resource allocation,

We are seeking a mission-driven Developer Relations Manager focused on Foundational AI Research to engage leading academic labs advancing the next generation of AI models, systems, and methods. In this role, you will work directly with top researchers building frontier AI systems, including large language models, multimodal models, reasoning systems, training methods, inference systems, model serving, and scalable AI infrastructure. You will help researchers adopt NVIDIA’s AI and accelerated computing platforms to push the boundaries of model performance, efficiency, and scale. The ideal candidate brings deep technical credibility in foundational AI, strong research engagement experience, and hands-on expertise in either AI inference research or AI training research. What you'll be doing: Serve as a trusted technical advisor to leading academic AI labs working on foundation models, LLMs, multimodal AI, reasoning, training, inference, and AI systems. Identify high-impact research workloads where NVIDIA software, systems, and accelerated computing platforms can advance model performance, scale, and efficiency. Engage principal investigators, postdocs, graduate researchers, and lab leadership to understand research goals, technical blockers, infrastructure needs, and collaboration opportunities. Track frontier AI research across papers, benchmarks, open-source projects, and academic labs to identify emerging trends and future platform opportunities. Partner with Research Account Managers, Solution Architects, Product, Engineering, and Business Development teams to support researcher adoption and long-term engagement. Represent researcher needs internally by translating academic feedback into actionable insights for product roadmaps, developer programs, education, and platform strategy. Support NVIDIA participation in major AI, ML, and systems research venues through technical content,