Systems Research Engineer Jobs

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,

About the Role Together AI is building the AI Native Cloud — an end-to-end platform for generative AI lifecycle, integrating fast, reliable inference, and model-shaping services with cutting-edge AI cloud infrastructure. We are looking for a seasoned Senior Technical Recruiter to partner closely with AI Research and Engineering leadership to scale world-class research teams across kernels, inference optimization, applied AI and model shaping. This role is ideal for someone who understands the unique dynamics of recruiting top-tier AI researchers and research engineers in a highly competitive market and can operate as a strategic talent partner to technical leadership. Responsibilities Partner with executives, research leadership, and hiring managers to define and execute hiring strategies Lead full-cycle recruiting for specialized AI talent, including researchers, research engineers, applied scientists, and ML systems engineers Build and nurture relationships with top AI talent across academia, open-source communities, research labs, and industry networks Drive exceptional candidate experiences from initial engagement through offer close, with a strong focus on relationship building and long-term talent cultivation Provide market intelligence on AI talent trends, compensation, competitive hiring landscapes, and emerging research organizations to influence hiring strategy and organizational planning Collaborate cross-functionally with sourcing, coordination, people operations, and leadership teams to continuously improve recruiting processes and operational excellence Design and refine interview processes tailored for research hiring, including technical evaluations, publication reviews, and research presentation loops Requirements 5+ years of technical recruiting experience at high-growth technology companies, with a proven track record hiring exceptional AI researchers, research engineers, applied scientists, or ML infrastructure talent at leading AI labs, hyper-sc

Perplexity is seeking top-tier AI Research Scientists and Engineers to advance our AI products and capabilities. We're building the future of AI-powered search and agent experiences through our Sonar models, Deep Research Agent, Comet Agent, and Search products. Join us in creating SOTA experiences that handle hundreds of millions of queries and continue to scale rapidly. Team Structure Depending on your interests and expertise, you'll work on one of three specialized teams: 1. Core Research Team (Horizontal) Focus on generating and improving base models that power all our products. This team works on foundational model capabilities, post-training techniques, building RL infra and infrastructure that benefits the entire organization. 2. Agent Products Team (Vertical) Concentrate on fine-tuning and optimizing models for our Deep Research Agent and Labs/Canvas products. This team bridges research and product, ensuring our agent capabilities deliver exceptional user experiences. 3. Comet Agent Team (Vertical) Dedicated to developing and enhancing our Comet Agent product. This specialized team focuses on the unique requirements and optimizations needed for Comet's specific use cases. Responsibilities Research & Development Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO) Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products Stay current with the latest LLM research, especially in model training, optimization, and personalization techniques Implement preference optimization and personalization capabilities to enhance user experience Invent in-house improvements and optimizations to enhance SOTA models Turn research ideas into algorithms and run experiments to launch new models Infrastructure & Implementation Own full-stack data, training, and evaluation pipelines required for model development Build robust and effective training frameworks (on

About the Role We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models. The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products. What you'll do Context Engineering: Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases. Build self-improvement loops to steer the prompt, improve tool/skill use, and improve the ability to draw on memory. Model Releases: Help experiment with and release new models. Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects, for both internal and production systems. Knowledge Sharing: Help engineers across teams build intuition for prompt design and context engineering best practices. Staying Current: Track the latest prompting, context engineering, and alignment techniques from industry and academia, and bring the best ideas back to the team. What We're Looking For Required 2 to 10+ years of experience in software engineering or research. Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems. Experience shaping LLM behavior through prompts, tool and skill design, or memory systems. Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders. Nice to have Recent experience working on modern LLM-driven products. Experience working across teams or with ext

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Program Overview Some of our world's grand challenges, from resolving long-open problems in mathematics to designing medicines for neglected diseases, require deep expert judgment that today's AI still lacks. We're working toward an AI scientist, a system capable of the long-horizon reasoning and experimental judgment needed to push the frontier on problems like these. We believe frontier AI, developed safely, can meaningfully accelerate progress across science and engineering. Getting there requires close collaboration with people who have spent years at the frontier of their fields. The Anthropic STEM Fellows Program brings researchers and experts from across science and engineering into Anthropic for four months to take on the grand challenges of their fields with Claude. Working in small pods of Fellows from related fields, you will pair deep domain expertise with our frontier models and internal tooling to define the hardest open problems in your discipline, build the datasets and simulations that let us test and train Claude on them, and find exactly where it falls short. We're looking for Fellows across science and engineering. Prior machine learning experience is helpful but not required. Scientific judgment and a willingness to learn quickly matter more. Our first cohort of more than 20 STEM Fellows across mathematics, physics, the life sciences, and engineering, ran from June to September 2026. The problems they built now feed Claude's training and one of our internal science evaluations. What to Expect: A place in a small pod of Fellows working on related problems in your domain. Your pod meets weekly with Anthropic researc

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Program Overview Many of the questions that will shape our future have no single checkable answer. Reasoning well about them, whether in law, policy, philosophy, economics, cognitive science, or AI safety itself, takes the kind of judgment experts spend years building. We believe frontier AI, developed safely, can become a real partner on these questions, but getting there means working closely with the people who know these fields best. This fellowship brings researchers and experts from philosophy, cognitive science, economics, policy, and law into Anthropic for four months to work alongside our research teams. Fellows pair deep domain expertise with our frontier models and internal tooling to evaluate, improve, and apply Claude's capabilities in their field. What to Expect: A concrete, scoped project matched to your background, with mentorship from Anthropic researchers. Access to frontier Claude models and internal evaluation tooling. A cohort of incoming Fellows to collaborate with and a connection to Anthropic's broader research community. Compensation: $100,000–$167,000 USD for the four-month fellowship (equivalent to $300,000–$500,000 USD annualized), and other benefits. Key responsibilities Identifying key open problems in your field, assessing approaches to solving them, and using Claude to make progress on them. Identifying grand societal challenges which the expertise of your field is crucial for addressing, and assessing Claude’s strengths and weaknesses in tackling them. Designing evaluations and RL environments that test models in your field systematically, turning your expertise into working tests of how well Cla

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We believe powerful AI can compress a century of scientific progress into a decade. Claude Science is a big part of building toward that future. Claude Science is an AI workbench that gives researchers a single environment for work that today spans dozens of disconnected tools — literature, specialized databases, scientific computing, analysis, and publication-ready outputs. Claude Science already renders protein structures, genome tracks, and chemical structures natively, and coordinates multi-agent workflows with built-in review for citation and calculation errors — and we're just getting started. Much of this is being built 0→1 right now, in a category no one has defined yet. We're growing the Claude Science product team. As a Product Manager on Claude Science, you will own a major area of the roadmap end to end — think expanding into new scientific fields, landing new model capabilities with researchers, or making the workbench ready for enterprise R&D teams — and help shape the overall product direction alongside the rest of the team. You'll spend real time with researchers in academic labs, biotech and pharma R&D, and research institutes to understand how science actually gets done — from hypothesis to analysis to publication and beyond— and turn what you learn into shipped product. You'll partner directly with our research teams to make the models better at science, help decide which fields and workflows we go after next, and shape what it takes for Claude Science to be trusted in enterprise and regulated research environm

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As part of our growing investment in building capabilities for drug discovery and development, we're looking for an exceptional biotech operator to help accelerate research in these areas. Our north star is to speed up progress in drug development by an order of magnitude, and this role is central to that goal: bringing sharp scientific judgment and operational expertise to identify where AI can have the greatest impact, and the drive to turn those insights into real results. This role is for an entrepreneurial operator with proven hands-on experience generating and translating therapeutic hypotheses in a biotech setting. You should be self-directed and multi-disciplinary - equally comfortable shaping the strategic direction of our life sciences work, partnering closely with our research, product, and go-to-market teams, or working hands-on with Claude, including tools like Claude Science, to explore hypotheses, design and analyze research, and demonstrate what's newly possible for scientists. The ideal candidate has grown up professionally in an organization that prioritizes scientific and executional rigor— for example, at a high-growth life sciences company or a leading science-focused investment or venture firm — and brings a rare blend of scientific depth, operating ability, and biotech fluency. Key responsibilities Identify and prioritize the areas where AI can most meaningfully accelerate life sciences research Turn promising scientific ideas into concrete, well-scoped efforts and see them through with speed and ownership Translate ambiguous scientific questions into structured, testable plans with clear mileston

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. Submit your application to the Economics & Policy workstream at the bottom of this page. We are accepting applications on a rolling basis for the next cohort expected to start in January 2027. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the January 2027 start date doesn't work for you. What to expect 4 months of full-time research Direct mentorship from Anthropic researchers Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) Substantial funding for compute and other research expenses Interview process The interview process will include an initial application, assessments, and interviews. We may ask for references later in the process as well. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing i

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Applications are now open for our January cohort - apply here by October 18. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect 4 months of full-time research Direct mentorship from Anthropic researchers Access to a shared workspace (in either Berkeley, California or London, UK) Connection to the broader AI safety and security research community Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit

About the Team The Alignment team at OpenAI is dedicated to ensuring that our AI systems are safe, trustworthy, and consistently aligned with human values, even as they scale in complexity and capability. Our work is at the cutting edge of AI research, focusing on developing methodologies that enable AI to robustly follow human intent across a wide range of scenarios, including those that are adversarial or high-stakes. We concentrate on the most pressing challenges, ensuring our work addresses areas where AI could have the most significant consequences. By focusing on risks that we can quantify and where our efforts can make a tangible difference, we aim to ensure that our models are ready for the complex, real-world environments in which they will be deployed. The two pillars of our approach are: (1) harnessing improved capabilities into alignment, making sure that our alignment techniques improve, rather than break, as capabilities grow, and (2) centering humans by developing mechanisms and interfaces that enable humans to both express their intent and to effectively supervise and control AIs, even in highly complex situations. About the Role As a Research Engineer / Research Scientist on the Alignment team, you will be at the forefront of ensuring that our AI systems consistently follow human intent, even in complex and unpredictable scenarios. Your role will involve designing and implementing scalable solutions that ensure the alignment of AI as their capabilities grow and that integrate human oversight into AI decision-making. This role is especially well suited for someone who can move from an ambiguous model-behavior question to a concrete experimental setup: formulate the hypothesis, build the evaluation or intervention, run the experiment, analyze the result, and decide what the evidence supports. This role may be based in San Francisco or London, subject to team needs and location approval. In this role, you will: We are seeking research engineers and res

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the alignment of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: Develop and publish research on techniques for understanding representations of deep networks. Engineer infrastructure for studying model internals at scale. Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter . Show enthusiasm for long-term AI safety & alignment, and have thought deeply about technical paths to safe AGI. Bring experience in the field of AI safety & alignment, mechanistic interpretability, or spiritually related disciplines. Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. Possess 2+ years of research engineering experience and proficiency in Python or similar languag

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: Develop and publish research on techniques for understanding representations of deep networks. Engineer infrastructure for studying model internals at scale. Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter . Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI. Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines. Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. Possess 2+ years of research engineering experience and proficiency in Python or similar languages. Are deeply curious. About OpenA

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic runs one of the largest and fastest-growing infrastructure fleets in the industry, across multiple accelerator families, CPU families, clouds, neoclouds, and on-prem sites. Capacity Engineering owns the data, tooling, and systems that let Anthropic plan, measure, and maximize utilization of that fleet: we partner on supply deals, wire telemetry from day zero, own the canonical capacity data layer, and build the planning and enforcement tools every research and product team relies on. This role sits in the Planning pillar, on the Demand Planning team, and works daily with research engineering, pretraining, inference, compute supply, finance, and external vendors. You own the tranches. The job has two halves that feed each other. Upstream, you take the Demand Planning forecast and turn it into per-tranche requirements — shape, interconnect, region, supporting resources, date — and carry those into sourcing negotiations and data center build reviews so we contract for capacity we can actually use when we need it. Downstream, you own the integrated schedule and system of record for every tranche in flight — from contracted through reserved, ingested, in-cluster, healthy, and occupied — and you drive the owners of each hop to their dates. Every slip you see downstream becomes a contract-language fix, an automation, or a correction fed back to the forecast. What you'll do Turn the forecast into per-tranche requirements. Take the Demand Planning forecast plus direct input from research, pretraining, and inference planners, and convert it into concrete accelerator, interconnect, region, supporting-resource, and date r

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight: Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful autonomy (for example future versions of auto-review ). About the Role We’re looking for strong executors with excellent judgment, comfort with ambiguity, and an understanding of frontier model research. You don’t need prior safety or alignment experience, we also welcome people that recently realized that alignment and safety is a critical area to contribute to. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Train and evaluate frontier models to reduce harmful or misaligned agent actions, forming clear hypotheses and executing independently through ambiguity. Mine incidents and build scalable measurement, data-processing, and evaluation systems that turn real failures into repeatable safety signals. Collaborate closely with post-training, capabilities, oversight, and pre-training partners to ship research-backed mitigations into large-scale training and agent systems. You might thrive in this role if you: Have demonstrated strength in research engineering, ML en