LLNL
Research
MachineLearningResearchEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Machine Learning Research Engineer at LLNL. Skills: Machine learning research, Applied machine learning, Scientific computing. Research new machine learning techniques. Develop new machine learning techniques”
Industry & Context.
Analytical; Problem-solving
What They're Looking For.
Must Have
M.S. in Computer Science, Applied Mathematics, or Statistics, Experience in at least one ML research area, Experience developing advanced ML models, Experience working with diverse teams, Comprehensive analytical skills, Comprehensive problem-solving skills
Nice to Have
Ph.D. in Computer Science, Applied Mathematics, or Statistics, Demonstrated research productivity, Advanced verbal communication skills, Advanced written communication skills, Experience with high-performance computing, Experience with GPU programming, Experience with parallel programming, Experience with cloud computing, Experience running numerical simulations, Experience with complex workflows, Experience with physics, Experience with biology, Experience with engineering, Background in statistics, Background in applied mathematics
What You'll Do.
Research new machine learning techniques
Develop new machine learning techniques
Implement new machine learning techniques
Evaluate new machine learning techniques
Adapt machine learning software stack
Deploy machine learning software stack
Participate in defining efforts
Participate in planning efforts
Participate in formulating efforts
Adapt machine learning research
Guide development of practical solutions
Collaborate with scientists
Collaborate with engineers
Provide guidance to experts
Explore potential for machine learning
Establish research directions
Author grant proposals
Present research results
Disseminate research results
How You'll Work.
Team & Collaboration
Multi-disciplinary teams; Cross-functional teams
Communication Scope
Scientific presentations; Technical reports; Scientific papers
Full Job Description
Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. We have an opening for Machine Learning Research experts to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society’s most important problems. You will work with or lead a multi-disciplinary team consisting of machine learning experts, data science practitioners, and domain scientists in areas ranging from fundamental research in machine learning, i.e., AI safety, robustness, uncertainty quantification, or interpretability to applied problems in fields such as high energy density physics, material science, predictive medicine, and treatment discovery. You will also have the opportunity develop and lead independent research thrust and engage with a variety of related research projects in parallel computing, data analysis and visualization, or applied mathematics. This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning techniques for multiple applications in a collaborative scientific environment. * Adapt and deploy common machine learning software stack on large-scale high performance computing clusters. * Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications. * Adap
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