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Applied Machine Learning - Analyst

Entry Level | Full-time
Engineering | livermore, CA | 08/23/2022

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Company Description

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.

Job Description

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.

Qualifications

  • Ability to secure and maintain a U.S. DOE X-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 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 successfully developing code that is well written, designed and documented.
  • 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.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Career Indefinite position. Lab employees and external candidates may be considered for this position.

Why Lawrence Livermore National Laboratory?

  • Included in 2022 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

Security Clearance

This position requires a Department of Energy (DOE) Q-level clearance.  If you are selected, 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.  Q-level 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.

Equal Employment Opportunity

LLNL is an equal opportunity employer that is committed to providing candidates and employees with a work environment free of discrimination and harassment. We value and hire a diverse workforce as it is a vital component of our culture and success. 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.

LLNL invites you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

Reasonable Accommodation

At LLNL, our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, 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.

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