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Applied Machine Learning - Analyst
Engineering | livermore, CA | 11/09/2021
Job Code: SES.1 Science & Engineering MTS 1 / SES.2 Science & Engineering MTS 2
Position Type: Career Indefinite
Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable
Join us and make YOUR mark on the World!
Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.
We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.
We are seeking highly qualified scientists and engineers to join our interdisciplinary team of Applied Machine Learning Analysts supporting a variety of application areas such as Cyber Security, Climate Modelling, Energy Systems, Bioscience and Advanced Manufacturing. Qualified candidates should have a working knowledge of standard machine learning toolkits as well as a background in a scientific discipline providing underlying skills in data analytic techniques. While supporting applied research projects, selected candidates will be provided mentorship and practical training to develop depth and breadth in machine learning techniques as well as gain exposure to a variety of application areas. These positions are in the Computational Engineering Division (CED) within the Engineering Directorate.
This position will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.
In this role you will
- Conduct data processing efforts, including but not limited to understanding the data through the use of visualization and statistical methods, cleaning/organizing the data, and applying state-of-the-art Machine Learning algorithms to real-world science and national security applications.
- Conduct paper/code surveys of state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
- Contribute to research efforts in Machine Learning to enable development of new state-of-the-art algorithms for Laboratory problem domains.
- Conduct experiments, training and validating new state-of-the-art Machine Learning algorithms for Laboratory problem domains.
- Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
- Participate in interactions with inter-organizational contacts and/or external customers.
- Assist in representing the organization by providing input on technical issues for specific projects including preparing and presenting technical reports.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.2 level
- Research, develop, and apply solutions to moderately complex Machine Learning problems of programmatic interest.
- Balance multiple projects/tasks and priorities of customers and partners to ensure deadlines are met, while working independently with minimal direction within scope of the assignment.
- Contribute to proposals.
- Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
- Bachelor’s degree in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics or the equivalent combination of education and related experience.
- Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).
- Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
- Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras or Caffe.
- Ability to work independently under general direction within the scope of an assignment and use sound judgment in determining methods, techniques, and evaluation criteria.
- Sufficient verbal and written communication skills necessary to effectively collaborate in a team environment and present technical ideas/results.
Additional qualifications at the SES.2 level
- Comprehensive knowledge and experience with Machine Learning algorithm development, with deep learning model development using PyTorch, TensorFlow, Keras, or Caffe, and with interactive web app development such as Flask or Bokeh.
- Experience successfully developing code that is well written, designed and documented.
- Proficient verbal and written communication skills to collaborate in a team environment, publish and present technical ideas at top-tier Machine Learning workshops or conferences, and inform management.
Why Lawrence Livermore National Laboratory?
- Included in 2021 Best Places to Work by Glassdoor
- Work for a premier innovative national Laboratory
- Comprehensive Benefits Package
- Flexible schedules (*depending on project needs)
- Collaborative, creative, inclusive, and fun team environment
Learn more about our company, selection process, position types and security clearances by visiting our Career site.
COVID-19 Vaccination Mandate
LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.
LLNL is a Department of Energy (DOE) and National Nuclear Security Administration (NNSA) Laboratory. Some positions will require a DOE L or Q clearance (please reference Security Clearance requirement above). If you are selected and a clearance is required, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. An L or Q clearance requires U.S. citizenship. For additional information please see DOE Order 472.2.
Pre-Employment Drug Test
External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Pre-Placement Medical Exam
A job related pre-placement medical examination may be required.
Equal Employment Opportunity
LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
LLNS is committed to offering reasonable accommodations during the application and recruiting processes due to a disability. If you need assistance or an accommodation due to a disability, please submit a request via our online form.
California Privacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.