Machine Learning Engineer - 91887
The National Energy Research Scientific Computing (NERSC, https://www.nersc.gov/) Center at Berkeley Lab is seeking a passionate Machine Learning Engineer to collaborate with scientists and conduct applied research and development, outreach and training in AI for Science.
We expect AI to be a major focus of computing within the Department of Energy's Office of Science in the coming decade. With Perlmutter, our upcoming GPU-based system to be brought online in 2021, and its successors, NERSC plans to offer the world's premier AI platform.
Your role will enable Office of Science researchers to benefit from the very latest machine learning and deep learning (ML/DL) techniques, conducted on some of the world's largest supercomputers, including Perlmutter. You will gain experience using cutting edge machine learning techniques and ‘Big Data' technologies and tools, operating at extreme-scales and work in a collaborative environment with scientists and engineers from a wide variety of backgrounds.
You will be part of NERSC's Data and Analytics Services group that supports experimental science and advanced analytics. You will also be part of multidisciplinary and cross-institution projects, involving academic and industry partners such as NVIDIA, HPE, Facebook and Google and renowned academics both in domain sciences as well as in machine-learning and statistics.
What You Will Do:
Support the ML/DL software stack on NERSC supercomputers, deploy new cutting edge tools and frameworks for scalable ML/DL workflows.
Collaborate with scientists and industry partners to develop new applications of machine learning for science - opening the door to new science.
Provide expert ML/DL advice, consultancy services, and training events to scientists and users of NERSC computing resources.
Engage with the ML academic communities to stay on top of the latest advancements in ML.
Shape future NERSC supercomputers, evaluating new hardware architectures for AI.
What is Required:
Bachelor's degree in Computational Science, Data Science, Computer Science, Applied Mathematics, Physical Sciences or a related science domain area and 5 years of related experience; or an equivalent combination of education and experience.
Experienced in machine learning and statistics, as applied to scientific data.
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.
Excellent communication and interpersonal skills.
Additional Desired Qualifications:
Advanced degree in Computational Science, Data Science, Computer Science, Applied Mathematics, Physical Sciences or a related science domain area and 3 years of related experience.
Familiarity with multiple deep learning architectures and technologies.
A proven track record of publications in Deep Learning at machine learning or domain science venues.
Familiarity with computing hardware, GPUs and/or AI accelerators.
Familiarity with performance profiling, benchmarking, optimization and scaling of DL architectures on HPC systems.
To be considered applicants are strongly encourage to include the following with their application:
A Cover Letter: Include a cover letter introducing yourself, your application, and describing your interest in the position.
Curriculum Vitae/Resume: Either an academic CV or a resume is acceptable. Be sure to highlight technical skills, publications, and activities, relevant to the position.
Links to public code repositories, project portfolios, blog posts or other relevant career metrics are welcome!
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.
This position may be 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.
Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
How To Apply
Apply directly online at http://188.8.131.52/counter.php?id=192603 and follow the on-line instructions to complete the application process.
Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here (https://www.dol.gov/agencies/ofccp/posters) to view the poster and supplement: "Equal Employment Opportunity is the Law."
Lawrence Berkeley National Laboratory encourages applications from women, minorities, veterans, and other underrepresented groups presently considering scientific research careers.