Research Scientist - Computer Vision and Machine Learning

Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

We have an opening for a Research Scientist in Computer Vision and Machine Learning to develop advanced algorithms and software for image and video understanding in support of problems of national importance. This role sits at the intersection of computer vision, image processing, software engineering and applied machine learning.

You will work in a collaborative, multidisciplinary environment alongside experts in computer vision, machine learning, scientific computing, and domain science. This role combines fundamental research with the development of robust, reproducible software systems that support mission-critical applications. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

This position will be filled at eitherlevel based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.

You will

• Conduct original research in computer vision, image processing, and machine learning.
• Develop, test, and evaluate algorithms for tasks such as segmentation, tracking, temporal reasoning, scene understanding, anomaly detection, multimodal fusion, and perception under uncertainty or occlusion.
• Build models and software that perform robustly on noisy and sparse data.
• Design and execute rigorous experiments, benchmarking strategies, and error analyses to assess model performance, reliability, and limitations.
• Develop research software using disciplined engineering practices, including code review, testing, documentation, version control, and traceability.
• Establish and maintain reproducible MLOpsworkflows for data preparation, experiment tracking, model and dataset versioning, automated training and evaluation, packaging, and deployment.
• Present results at reviews, seminars, and scientific meetings, and publish in peer-reviewed venues as appropriate.
• Perform other duties as needed.

Additional job responsibilities, at the SES.
3 level

• Provide technical leadership and guidance to multiple diverse, technical teams of LLNL scientists and engineers to operationalize research and development advancements for LLNL national security programs, while executing projects and tasks and balancing priorities of customers and partners to ensure deadlines are met.
• Independently determine technical objectives and criteria to satisfy project deliverables and execute the appropriate technical approaches.
• Oversee the activities of other personnel, providing informal mentoring and guidance to less-experienced team members.

Qualifications

• Ability to secureand maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Master's degree in computer science, data science, applied mathematics, or a related field with emphasis in machine learning, image processing, or scientific computing, or the equivalent combination of education and related experience .
• Comprehensive knowledge and experience in computer vision and machine learning, especially for image or video data.
• Experience with Python programming skills and comprehensive experience in applied machine learning, including developing and evaluating models using PyTorch or Tensor Flow.
• Demonstrated experience with reproducible ML workflows, experiment tracking, model and dataset versioning, automated evaluation and testing.
• Experience with AI coding agents to support agentic development, accelerate research iteration, automate experimentation, and enable reproducible software development.
• Proficient verbal and written communication skills necessary to effectively collaborate in a multi-disciplinary team.
• Demonstrated analytical, problem-solving, and decision-making skills to effectively develop creative solutions to moderately complex problems.
• Ability to travel off-site for sponsor and customer interactions.

Additional qualifications at the SES.
3 level

• PhD in computer science, data science, applied mathematics, or a related field with emphasis in computer vision, machine learning, image processing, or the equivalent combination of education and related experience.
• Advanced level knowledge in one or more of the following areas: computer vision, video object segmentation, multi-object tracking.
• Advanced…