Machine Learning Researcher

LLNL$210K — $320K *
Education, Government & Non-Profit
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in Computer Science, Applied Mathematics, Statistics, or related field, or equivalent experience.
  • 8+ years post-PhD experience in machine learning and data analysis research.
  • Significant expertise in foundational or applied machine learning and large-scale data analysis.
  • Proficient in developing and applying advanced statistical tools and machine learning models using C++, PyTorch, TensorFlow, etc.
  • A strong publication record in high-impact scientific venues such as IEEE Transactions, NeurIPS, ICML, PNAS, etc.
  • Proven ability to work with diverse teams to solve complex problems.
  • Experience leading research teams and developing strategic engagements.

Responsibilities

  • Establish independent research thrusts through strategic partnerships.
  • Lead research teams in applied machine learning and data analysis.
  • Provide strategic guidance and technical leadership to management.
  • Research and implement new machine learning techniques in collaborative environments.
  • Collaborate with scientists to define and formulate experimental efforts.
  • Guide subject matter experts to explore machine learning applications.
  • Adapt machine learning research for real-world, high-stakes scenarios.

Benefits

  • Flexible work arrangements.
  • Opportunities for professional growth and development.
  • Access to cutting-edge technology and facilities.
  • Engagement with diverse teams across scientific disciplines.
  • Involvement in high-impact national security applications.
Full Job Description
Job Description

We have an opening for a Machine Learning and Data Analysis expert to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important problems. You will work with and lead multi-disciplinary teams consisting of machine learning experts, data science practitioners, analysis experts, and domain scientists in areas ranging from fundamental research in machine learning, development, deployment, and performance optimization of large scale AI models, to applied AI and analysis problems in fields such as high energy density physics, material science, predictive medicine, and treatment discovery. You will also have the opportunity develop research strategies in these areas and engage with a variety of related research projects in parallel computing, data analysis and visualization, or applied mathematics. This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate.

Essential Duties
  • 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 in support of one or more 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 for multiple applications in a collaborative scientific environment.
  • Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications.
  • Provide guidance to subject matter experts in various fields to jointly explore the potential for machine learning research to solve domain specific challenges.
  • Adapt current machine learning research to real world applications at scale, with potentially limited and noisy data, with a high consequence of error, and guide the development of 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 accomplish research goals.
  • Perform other duties as assigned.

In Addition, At SES.5 Level
  • Provide scientific and technical direction for large projects and programs.
  • Support lab leadership in attracting retaining projects, programs, funding, and staff.
  • Engage and influence senior management, policy makers, and external sponsors.

Qualifications
  • Ph.D. in Computer Science, Applied Mathematics, Statistics or related field or the equivalent combination of education and related experience.
  • 8+ years of experience post PhD in research in machine learning and data analysis
  • Significant experience in foundational or applied machine learning research area and large scale data analysis.
  • Experience independently developing, implementing, and applying advanced statistical tools, machine learning models, and data analysis algorithms using modern software libraries such as C++, PyTorch, TensorFlow, or similar as evidence through medium to large scale models, applications, and experiments.
  • Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in high impact venues, such as, IEEE Transactions, NeurIPS, ICML, MLST, PNAS, etc.
  • Significant experience in working with diverse teams to solve complex problems and deliver practical solutions.
  • Substantial record of sustained program development and strategic engagement in fields related to machine learning and data analysis.
  • Experience leading research teams in achieving long term objectives and delivering solutions.
  • Expert verbal and written communication and interpersonal skills necessary to effectively collaborate with internal and external teams to present and explain technical information and to advise senior management and external sponsors.
  • Experience in working with subject matter experts in one or more areas, such as physics, biology, or engineering.

In Addition, at the SES.5 Level
  • Record of sustained engagement with regulators, funding agencies, top level management, or other oversight agencies.
  • Demonstrated record of program development in machine learning, data analysis, or related fields.
  • Experience providing scientific and technical directions to R&D teams delivering innovative approaches with significant impact and internal and external recognition.

Desired Qualifications
  • Experiencewith high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations or complex workflows

Pay Range

$210,630 - $320,580 Annually

$210,630 - $267,060 Annually for the SES.4

$252,810 - $320,580 Annually for the SES.5

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage.An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Flexible Term appointment, which is for a definite period not to exceed six years.If final candidate is a Career Indefinite employee, Career Indefinite status may be maintained (should funding allow).

Security Clearance

None required.However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check.

National Defense Authorization Act (NDAA)

The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the useand/or possession ofmobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area whereyou are not permitted to have a personal and/or laboratory mobile devicein your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

Ifyou useamedical device, whichpairs with a mobile device,you must still follow the rules concerningthe mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities requireseparate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

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