The National Energy Research Scientific Computing (NERSC) 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:
PhD 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 encouraged to include the following with their application by Feb 26, 2021 :
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.
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 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.
Internal Number: 91887
About Lawrence Berkeley National Laboratory
In the world of science, Lawrence Berkeley National Laboratory (Berkeley Lab) is synonymous with excellence. Thirteen scientists associated with Berkeley Lab have won the Nobel Prize. Fifty-seven Lab scientists are members of the National Academy of Sciences (NAS), one of the highest honors for a scientist in the United States. Thirteen of our scientists have won the National Medal of Science, our nation's highest award for lifetime achievement in fields of scientific research. Eighteen of our engineers have been elected to the National Academy of Engineering, and three of our scientists have been elected into the Institute of Medicine. In addition, Berkeley Lab has trained thousands of university science and engineering students who are advancing technological innovations across the nation and around the world. Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (UC) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 200-acre site in the hills above the UC Berkeley campus that offers spectacular... views of the San Francisco Bay, Berkeley Lab employs approximately 4,200 scientists, engineers, support staff and students. Its budget for 2011 is $735 million, with an additional $101 million in funding from the American Recovery and Reinvestment Act, for a total of $836 million. A recent study estimates the Laboratory's overall economic impact through direct, indirect and induced spending on the nine counties that make up the San Francisco Bay Area to be nearly $700 million annually. The Lab was also responsible for creating 5,600 jobs locally and 12,000 nationally. The overall economic impact on the national economy is estimated at $1.6 billion a year. Technologies developed at Berkeley Lab have generated billions of dollars in revenues, and thousands of jobs. Savings as a result of Berkeley Lab developments in lighting and windows, and other energy-efficient technologies, have also been in the billions of dollars. Berkeley Lab was founded in 1931 by Ernest Orlando Lawrence, a UC Berkeley physicist who won the 1939 Nobel Prize in physics for his invention of the cyclotron, a circular particle accelerator that opened the door to high-energy physics. It was Lawrence's belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab legacy that continues today.