Research Scientist - Computer Vision and Machine Learning

LLNL•Livermore, CA

7d•Hybrid

About The Position

Lawrence Livermore National Laboratory (LLNL) is seeking 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 is at the intersection of computer vision, image processing, software engineering, and applied machine learning, within a collaborative, multidisciplinary environment. The position combines fundamental research with the development of robust, reproducible software systems for mission-critical applications. This role is in the Computational Engineering Division (CED), within the Engineering Directorate. Depending on assignment, this position may offer a hybrid schedule, blending in-person and virtual presence, with the flexibility to work from home one or more days per week. The position will be filled at either the SES.2 or SES.3 level based on knowledge and related experience.

Requirements

Ability to secure and 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 TensorFlow.
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.
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 (SES.3 level).
Advanced level knowledge in one or more of the following areas: computer vision, video object segmentation, multi-object tracking (SES.3 level).
Advanced leadership skills and experience and demonstrated ability to exercise independent judgment to effectively manage diverse technical teams in executing projects (SES.3 level).
Ability to independently develop and execute complex analyses and to prepare and finalize tailored reports (SES.3 level).
Advanced verbal and written communication skills necessary to effectively collaborate in a multidisciplinary team and present technical information to a variety of audiences (SES.3 level).

Nice To Haves

Experience in one or more of the following: video understanding, multi-object tracking, segmentation, scientific imaging, remote sensing, sensor fusion, multimodal learning, or autonomous perception.
Experience deploying or sustaining computer vision or ML systems in operational or mission-critical environments.
Experience working with high-performance computing, distributed training, or large-scale data processing environments.
Experience maintaining or modernizing codes while preserving reliability and continuity of operations.
Familiarity with secure, regulated, or high-consequence research and engineering environments.
Ability to balance exploratory research with delivery, documentation, validation, and stakeholder needs.

Responsibilities

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 MLOps workflows 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.
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 (SES.3 level).
Independently determine technical objectives and criteria to satisfy project deliverables and execute the appropriate technical approaches (SES.3 level).
Oversee the activities of other personnel, providing informal mentoring and guidance to less-experienced team members (SES.3 level).