Machine Learning Engineer

Lawrence Berkeley National Lab's (LBNL) NERSC Division has an opening for a Machine Learning Engineer to join the team.

In this exciting role, you will serve as a Machine Learning Engineer in NERSC's Data and AI Services group. We are building a next-generation platform for scientific AI on supercomputers. You will apply broad expertise to develop AI services to support science. You will be a part of multidisciplinary and cross-institution projects, involving lab, academic and industry partners. Responsibilities could include developing new AI services and supporting the AI software stack on NERSC supercomputers; deploying new cutting-edge tools and frameworks for at-scale scientific AI workflows; and working with scientists to apply AI techniques to their research.

The selected candidate(s) will be hired at the Computer Systems Engineer 3 or 4 (CSE3 or CSE4) depending on their level skills and experience. When applying, a cover letter is highly encouraged.

What You Will Do, at Level 3:

• Develop AI services on NERSC's advanced computing and data systems to support fundamental science

• Support the AI software stack on NERSC supercomputers, deploy new cutting-edge tools and frameworks for scalable AI workflows.

• Provide expert AI engineering engagement, and training events to scientists and users of NERSC computing resources.

• Engage with the AI community to stay on top of the latest advancements in AI services and software

• Shape future NERSC supercomputers, evaluating new architectures for AI.

• Collaborate with scientists and industry partners to enable transformative AI for science

• Determine methods and procedures on new assignments and may coordinate activities of other personnel.

• Network with key contacts outside your own area of expertise.

• Work on and resolve complex issues where analysis of situations or data requires an in-depth evaluation of variable factors.

• Exercise judgment in selecting methods, techniques and evaluation criteria for obtaining results.

Additional Responsibilities, at Level 4:

• Mentor and lead early career staff members in AI services, techniques and projects

• Stay abreast of new and emerging trends in AI services, through collaborations, workshops and conferences; translate these new directions into actionable opportunities for NERSC or NERSC users.

• Develop strategy for addressing both performance, as well as productivity requirements of the NERSC AI for science community.

• Work on and resolve significant and unique issues where analysis of situations or data requires an evaluation of intangibles.

• Exercise independent judgment in methods, techniques and evaluation criteria for obtaining results.

What is Required, at Level 3:

• Bachelor's degree in Physical Sciences, Computer Science or related field or equivalent is required. Masters and PhD degrees in similar disciplines are preferred.

• Typically requires a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or equivalent experience.

• Wide-ranging experience in the areas of AI and/or data science, as applied to scientific data.

• Ability to troubleshoot and resolve complex issues in creative and effective ways.

• Ability to network and collaborate with key contacts outside their own area of expertise.

• Excellent oral and written communication skills.

• Excellent software development skills

• Proven ability to work productively both independently and as part of an interdisciplinary team balancing divergent objectives involving research, code development, supporting software and consulting with scientists.

Additional Requirements, at Level 4:

• Typically requires a minimum of 12 years of related experience with a Bachelor's degree; or 8 years and a Master's degree; or equivalent experience.

• Broad expertise and/or unique knowledge in the areas of AI technology is required.

• Ability to work on and resolve significant and unique issues where analysis of situations or data requires an evaluation of intangibles.

• Ability to exercise independent judgment in methods, techniques and evaluation criteria for obtaining results.

Desired Qualifications:

• Familiarity with deep learning architectures and technologies (e.g., TensorFlow, PyTorch, JAX).

• Track record of AI software development, AI service deployments, or publications in AI/science venues.

• Experience with GPUs and performance optimization of ML at scale.

• Familiarity with containerization and HPC workflows.

Notes:

• This is a full-time, career appointment, exempt (monthly paid) from overtime pay.

• This position will be hired at a level commensurate with the business needs and the skills, knowledge, and abilities of the successful candidate.

• Salary range

• Level 3: The full salary range of this position is between $136,440 to $230,244 per year and is expected to pay between a targeted range of $153,492 to $187,596 per year depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.

• Level 4: The full salary range of this position is between $155,388 to $262,224 per year and is expected to pay between a targeted range of $174,804 to $213,660 per year depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.

• This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

• This position requires substantial on-site presence, but is eligible for a flexible work mode, and hybrid schedules may be considered. Hybrid work is a combination of performing work on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA and some telework. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab. Work schedules are dependent on business needs. In rare cases, full-time telework or remote work modes may be considered. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites.

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.

Berkeley Lab is a University of California employer. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor.

Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.