Machine Learning (ML) Bioengineer

Join Lawrence Livermore National Laboratory (LLNL) and contribute to impactful work advancing science and technology in national security. Our mission covers nuclear deterrence, threat preparedness, energy security, and multi-domain defense, fostering a culture of innovation and operational excellence where your expertise can drive real-world change.

About the role

We have an opening for a Machine Learning (ML) Bioengineer to conduct research, training, and evaluation of next-generation clinical, protein, and genome language models. You will join the Bioresilience Incubator, integrating predictive computational modeling, machine learning, and experimental biology to advance national security and public health missions. This position is within the Computational Engineering Division (CED), Engineering Directorate, and matrixed to the Bioresilience Incubator.

As part of a multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, interfacing with experimentalists generating large datasets via novel high-throughput assays. You will leverage in-house computational tools and contribute to designing, training, and evaluating new machine-learning methods. This role may offer a hybrid schedule, blending in-person and virtual work.

This position may be filled at either the SES.2 or SES.3 level, depending on knowledge and experience.

Responsibilities

• Collaborate with project scientists and engineers to develop, implement, and evaluate computational frameworks and models.
• Contribute to the development and application of advanced analysis methodologies; analyze data; document research through presentations and peer-reviewed publications.
• Support technical activities for new capability development and provide solutions to moderately complex to complex technical problems using established and innovative methods.
• Contribute to the completion of project milestones, influencing the development of organizational goals and objectives.
• Establish, implement, and maintain quality standards for project deliverables.
• Contribute to briefings and presentations documenting project activities and research results.
• Routinely interact with technical contacts at sponsor and partner organizations; represent the organization on specific technical projects.
• Participate in the development of future research directions and proposals to secure ongoing projects in computational protein design.
• Balance multiple projects/tasks and priorities to ensure deadlines are met, working independently with minimal direction within the scope of assignments.
• Perform other duties as assigned.

Additional Responsibilities at the SES.3 Level

• Determine, propose, and implement advanced analysis methodologies and contribute to identifying future research directions and proposals that will secure future projects in the field.
• Guide the completion of projects and influence the development of organizational goals and objectives.
• Lead the development of briefings and presentations documenting project activities and research results.
• Represent the organization as the primary technical contact on tasks and projects, serving on internal technical/advisory committees and potentially on external committees.
• Oversee the activities of other personnel, providing informal mentoring and guidance to less-experienced team members.
• Contribute to and influence the development of innovative projects, principles, and ideas in computational protein design.

Requirements

• Ability to secure and maintain a U.S. DOE Q-level security clearance, which requires U.S. citizenship.
• Master’s degree in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics, or a related field, or the equivalent combination of education and related experience.
• Comprehensive knowledge and experience developing and applying algorithms in one or more of the following machine learning areas: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning.
• Experience developing and implementing deep learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar, as evidenced by publications or software releases.
• Experience with high-performance computing, multi-node, multi-GPU, distributed training.
• Comprehensive knowledge in protein and genome language models sufficient to communicate effectively with team members and subject matter experts.
• Proficient verbal and written communication skills necessary to collaborate within a team environment and present technical information to varied audiences.
• Effective interpersonal skills and initiative necessary to interact with all levels of personnel and work independently in a collaborative, multidisciplinary team environment.
• Demonstrated ability to balance multiple projects and prioritize competing demands while maintaining high-quality standards for deliverables.

Additional Qualifications at the SES.3 Level

• Advanced knowledge and experience in developing and applying algorithms in machine learning areas.
• Significant experience developing and implementing medium to large-scale deep learning models and algorithms using modern software libraries.
• Demonstrated ability to provide guidance and informal mentoring to other personnel and junior team members.
• Advanced verbal and written communication skills necessary to effectively collaborate in a multidisciplinary team and present technical information to a variety of audiences.
• Demonstrated ability to represent the organization as a primary technical contact and to contribute to the development of innovative projects, principles, and ideas.

Qualifications We Desire

• PhD in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field.
• Strong understanding of protein and genome language models and datasets.
• Experience publishing research results in peer-reviewed scientific journals and presenting at conferences and workshops.
• Experience with GPU programming and running complex workflows.

Pay

$146,340 - $222,564 annually. Specific ranges are:

• $146,340 - $185,544 annually for the SES.2 level.
• $175,530 - $222,564 annually for the SES.3 level.

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

Benefits

• Included in 2026 Best Places to Work by Glassdoor.
• Flexible Benefits Package.
• 401(k).
• Relocation Assistance.
• Education Reimbursement Program.
• Flexible schedules (*depending on project needs).

For more details, visit LLNL Values.