Machine Learning Researcher

Join us and make your mark on the world! Lawrence Livermore National Laboratory (LLNL) advances science and technology to strengthen U.S. security and promote global stability. Our mission spans nuclear deterrence, threat preparedness, energy security, and multi-domain defense, empowering teams to tackle today’s and tomorrow’s toughest challenges. With a culture built on innovation and operational excellence, LLNL is where your expertise can drive real impact.

About the role

We have an opening for a Machine Learning and Data Analysis expert to advance the discipline and apply cutting-edge tools to critical societal problems. You will collaborate with and lead multidisciplinary teams of machine learning experts, data scientists, analysts, and domain scientists in areas such as fundamental machine learning research, development and deployment of large-scale AI models, and applied AI for high energy density physics, material science, predictive medicine, and treatment discovery. You will also shape research strategies and engage with projects in parallel computing, data analysis, visualization, and applied mathematics. This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate.

Responsibilities

• Establish independent research thrusts through strategic engagements with internal and external sponsors.
• Lead mid- to large-sized research teams in applied machine learning and data analysis for mission-related scientific applications.
• Provide strategic guidance to LLNL management and demonstrate technical leadership in the research community.
• Research, develop, implement, and evaluate new machine learning and data analysis techniques in a collaborative scientific environment.
• Define, plan, and formulate experimental, modeling, and simulation efforts for complex national security problems alongside project scientists and engineers.
• Guide subject matter experts in exploring machine learning solutions for domain-specific challenges.
• Adapt machine learning research to real-world applications at scale, addressing limited or noisy data and high-consequence errors, while developing practical solutions.
• Present and disseminate research results at scientific conferences and in peer-reviewed publications.
• Establish future research directions and author grant proposals, including presentations to programmatic sponsors and external funding agencies.
• Collaborate with a broad spectrum of scientists and engineers, internally and externally, to achieve research goals.
• Perform other duties as assigned.

Additional Responsibilities at SES.5 Level

• Provide scientific and technical direction for large projects and programs.
• Support lab leadership in attracting, retaining, and securing projects, programs, funding, and staff.
• Engage and influence senior management, policymakers, and external sponsors.

Qualifications

• Ph.D. in Computer Science, Applied Mathematics, Statistics, or a related field, or equivalent combination of education and experience.
• 8+ years of post-PhD experience in machine learning and data analysis research.
• Significant experience in foundational or applied machine learning research and large-scale data analysis.
• Experience developing, implementing, and applying advanced statistical tools, machine learning models, and data analysis algorithms using modern software libraries (e.g., C++, PyTorch, TensorFlow) demonstrated through medium- to large-scale models and experiments.
• Demonstrated research productivity, as evidenced by publications, reports, presentations, or open-source software in high-impact venues (e.g., IEEE Transactions, NeurIPS, ICML, MLST, PNAS).
• Significant experience working with diverse teams to solve complex problems and deliver practical solutions.
• Substantial record of sustained program development and strategic engagement in machine learning and data analysis.
• Experience leading research teams to achieve long-term objectives and deliver solutions.
• Expert verbal and written communication and interpersonal skills for collaborating with internal and external teams, presenting technical information, and advising senior management and sponsors.
• Experience working with subject matter experts in fields such as physics, biology, or engineering.

Additional Qualifications at SES.5 Level

• Record of sustained engagement with regulators, funding agencies, top-level management, or oversight bodies.
• Demonstrated record of program development in machine learning, data analysis, or related fields.
• Experience providing scientific and technical direction to R&D teams delivering innovative approaches with significant impact and recognition.

Desired Qualifications

• Experience with high-performance computing, GPU programming, parallel programming, cloud computing, or related methods, including running numerical simulations or complex workflows.

Pay

Pay range: $210,630 – $320,580 annually.
SES.4 level: $210,630 – $267,060 annually.
SES.5 level: $252,810 – $320,580 annually.
This reflects the lowest to highest salary we believe we would pay for this role at the time of posting. Pay will not be below any applicable local minimum wage. An employee’s position within the range depends on competencies, education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business needs.

Schedule

This is a Flexible Term appointment, lasting up to six years. If the final candidate is a Career Indefinite employee, Career Indefinite status may be maintained (funding permitting).

Benefits

• Flexible benefits package
• 401(k)
• Relocation assistance
• Education reimbursement program
• Flexible schedules (depending on project needs)

Learn more about our values at LLNL’s Inclusion Page.

Additional Information

No security clearance is required initially. However, if your assignment exceeds 179 cumulative days within a calendar year, you must complete the Personal Identity Verification process, including an online background investigation and approval.

The 2025 National Defense Authorization Act (NDAA), Section 3112, restricts access to specific non-public areas of national security or nuclear weapons facilities for citizens of China, Russia, Iran, and North Korea without dual U.S. citizenship or legal permanent residence. Eligibility for this position requires compliance with Section 3112.

External applicants selected for this position must pass a post-offer, pre-employment drug test, including testing for marijuana use, as federal law applies to LLNL as a federal contractor.

Depending on job duties, work in Limited Areas may restrict the use or possession of personal or laboratory mobile devices, including cell phones, tablets, fitness devices, and wireless headphones. Medical devices paired with mobile devices must comply with these restrictions unless wireless capabilities are disabled. Hearing aids without wireless features are permitted. Separate approval is required for Sensitive Compartmented Information Facilities.