Systems Phd Jobs

POSITION SUMMARY: Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing. PRIMARY RESPONSIBILITIES: Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features Develop multimodal AI architectures that integrate H&E whole-slide imaging data with molecular and clinical data sources Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS) Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools Analyze model outputs to generate reproducible biological and clinical insights Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders QUALIFICATIONS: PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics Hands-on expertise with PyTorch and

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

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in Canada; visa sponsorship is not available for this role. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. Join the HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who Should Apply Professional and Academic Background: 5+ years of software engineering or related technical experience, or equivalent domain expertise through academic work (e.g. PhD, postdoctoral research, or faculty experience in Computer Science or related field). Skills: Demonstrated coding proficiency and analytical abilities, with deep expertise in one or more of the following programming languages: Python, Java, Rust, Swift, JavaScript, or C++. Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration. Why

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply Professional and Academic Background: 5+ years of software engineering or related technical experience, or equivalent domain expertise through academic work (e.g. PhD, postdoctoral research, or faculty experience in Computer Science or related field). Skills: Demonstrated coding proficiency and analytical abilities, with deep expertise in one or more of the following programming languages: Python, Java, Rust, Swift, JavaScript, or C++. Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply Professional and Academic Background: 5+ years of software engineering or related technical experience, or equivalent domain expertise through academic work (e.g. PhD, postdoctoral research, or faculty experience in Computer Science or related field). Skills: Demonstrated coding proficiency and analytical abilities, with deep expertise in one or more of the following programming languages: Python, Java, Rust, Swift, JavaScript, or C++. Professional Mindset: Detail-oriented, innovative thinker with a

About the Team Our DD Labs team builds real-time autonomous delivery systems. The Planning & Decision-Making group is investing heavily in deep reinforcement learning to move beyond classical planning, learning policies that generalize across novel driving scenarios, handle long-tail edge cases, and improve continuously from large-scale fleet data. Our models jointly handle prediction and planning in a single unified architecture. Our stack is pure JAX end-to-end: the same code you train with is the code that runs on the robot. No C++ rewrites, no TensorRT export. A new policy goes from training to on-vehicle deployment in minutes. About the Role As a Senior/Staff Deep RL Engineer, you will design, train, and deploy deep reinforcement learning policies that make real-time driving decisions for our autonomous vehicles. You will own the full lifecycle, from problem formulation and reward design through large-scale distributed training to on-vehicle inference. You'll help define how learned components compose with the rest of the autonomy stack to produce robust, shippable behavior. You’re excited about this opportunity because you will… Formulate complex driving tasks as RL problems with well-shaped reward functions and expressive state/action representations. Design and train model-based deep RL agents using GPU-accelerated simulation at massive scale, including improving the simulator itself. Build and maintain distributed training infrastructure in JAX across large compute clusters. Build agentic optimization systems that automatically improve code, run experiments, analyze metrics, and iterate on RL policies with minimal human intervention. We’re excited about you because… BS/MS/PhD in CS, EE, Robotics, or a related field, with a strong foundation in reinforcement learning and deep learning. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing,

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Develop and evaluate complex financial scenarios to test and enhance AI accuracy in valuation, forecasting, and analysis; collaborate in interactive sessions to assess model outputs for market relevance and compliance; provide detailed feedback to improve AI capabilities; and contribute to specialized projects in financial modeling, risk assessment, and equity research. HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply Education: PhD, Master, BBA in Finance, Economics, or related degrees. Certifications: CFA or CPA strongly preferred. Professional Background: 5+ years in FP&A, Investment Banking, Portfolio Management, Financial Consulting, or equivalent research experience. Skills: Strong proficiency in financial modeling, valuation methodologies, forecasting, as

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply Education: PhDs, postdoctoral researchers, and professors with domain expertise in STEM fields such as Computer Science, Machine Learning, Physics, Biology, Chemistry, Mathematics, Humanities, or other related disciplines. Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration. Why Join the HFC? Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research—while deepening their AI expertise, str

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 is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities: Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development Independently lead small research projects while collaborating with team members on larger initiatives Design, run, and analyze scientific experiments to advance our understanding of large language models Optimize and scale our training infrastructure to improve efficiency and reliability Develop and improve dev tooling to enhance team productivity Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications: Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field Strong software engineering skills with a proven track record of building complex systems Expertise in Python and experience with deep learning frameworks (PyTorch preferred) Familiarity with large-scale machine learning, particularly in the context of language models Ability to balance research goals with practical engineering constraints Strong problem-solving skills and a results-oriented mindset Excellent communication skills

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Develop and evaluate complex financial scenarios to test and enhance AI accuracy in valuation, forecasting, and analysis; collaborate in interactive sessions to assess model outputs for market relevance and compliance; provide detailed feedback to improve AI capabilities; and contribute to specialized projects in financial modeling, risk assessment, and equity research. HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply Education: PhD, Master, BBA in Finance, Economics, or related degrees. Certifications: CFA or CPA strongly preferred. Professional Background: 5+ years in FP&A, Investment Banking, Portfolio Management, Financial Consulting, or equivalent research experience. Skills: Strong proficiency in financial modeling,

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 is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pretraining team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities: Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development Independently lead small research projects while collaborating with team members on larger initiatives Design, run, and analyze scientific experiments to advance our understanding of large language models Optimize and scale our training infrastructure to improve efficiency and reliability Develop and improve dev tooling to enhance team productivity Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications: Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field Strong software engineering skills with a proven track record of building complex systems Expertise in Python and experience with deep learning frameworks (PyTorch preferred) Familiarity with large-scale machine learning, particularly in the context of language models Ability to balance research goals with practical engineering constraints Strong problem-solving skills and a results-oriented mindset Excellent communication skills a

Adobe Firefly’s Generative AI Services team is seeking a Senior Staff Machine Learning Engineer for our GenAI Services area. In this high-impact role, you will work with a team of talented engineers in building scalable, high-performance generative AI systems—powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere. You will design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe’s first-party and third-party generative models into Adobe suite of products that serve individual and enterprise customers. You will tackle Adobe’s most complex engineering challenges at the forefront of the the industry, set technical direction, and mentor other ML engineers. Job Responsibilities Design and Development of core GenAI services and APIs that integrate a wide range of generative models into Adobe’s flagship products. Design and build ML workflows for enterprise-scale model customization, serving, and ecosystem integration. Collaborate with Adobe Research and other model developer teams with a focus on model inference strategies and productization of those model Build and optimize GPU-accelerated pipelines for both (customized) model training and inference—prioritizing performance, scalability, and reliability. Foster a culture of innovation , technical excellence, and continuous improvement across the organization. What You’ll Need to Succeed MS or PhD in Computer Science, Machine Learning, or a related field—or equivalent industry experience. 10+ years of experience in machine learning, including production-scale deployments. 3+ years of experience leading large-scale, GPU-intensive GenAI systems (training,

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! Research Fellow About the Role As a Research Fellow at Snorkel, you’ll build open benchmarks and evaluation environments that help shape how AI progress is measured. This fellowship is for PhD students and postdocs who want to turn important questions in their fields into new ways to evaluate AI capabilities. You’ll own the project from the initial research question through public release, setting its direction and leading its development. A Snorkel researcher will serve as your co-advisor, and you’ll have access to Snorkel’s broader resources, including paid time from credentialed domain experts and compute to run experiments and evaluate frontier models. You’ll retain your academic affiliation while spending at least one day a week with Snorkel’s research team, including in person in our San Francisco or New York offices where applicable. What you’ll do Scope and lead a new benchmark, dataset, or environment in a domain where current evaluations fall short Define the task specification, rubrics, and reference answers with domain experts from Snorkel's network, and run the expert review process Release the research artifact publicly, with you as lead author. Join weekly research meetings to share progress, receive feedback, and contribute to other researchers’ projects What you'll get A Snorkel research co-advisor matched to your project Domain Experts, compute, and engineering support for your project An open-source academic artifact released as

NVIDIA’s Executive Briefing Center (EBC) Solutions Architect (SA) team is looking for a highly hands-on Solutions Architect with exemplary communication skills. The role involves developing, demonstrating (in the NVIDIA EBC), and packaging agentic AI systems. Partnering with account SAs you will co-develop proof of concepts (POC) and "uplift" their presentation quality to match the NVIDIA branding and messaging used with Executive meetings. This is a builder’s and presenter's role! You will spend time architecting and writing code. You will develop multi-agent systems, retrieval pipelines, and optimized inference stacks on NVIDIA’s full-stack accelerated computing platform. We want a creative, diligent, and curious engineer energized by agentic AI and ready to make significant change. If that’s you, join us! What you’ll be doing: Architect, build, and ship end-to-end Agentic AI applications for a variety of use cases—spanning multi-agent coordination, long-horizon reasoning, planning, and tool use. Act as Technical Advisor alongside fellow Subject Matter Experts (SME) in Executive Briefings. Creating and presenting demos that are used at Trade Shows or Customer Meetings. Partner with NVIDIA engineering, product, and sales teams to secure build wins, translate customer feedback into actionable product and roadmap insights, and scale global expertise through technical collateral, workshops, and developer communities. What we need to see: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience) 2+ years as an ML/Software Engineer or Solutions Architect writing production-level code in Python and/or C/C++ in Linux environments. Validated experience building sophisticated agentic and multi-agent AI sy

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated