Machine Learning Engineer

We have an opening for a Machine Learning Engineer to collaborate with our research software teams. You will develop and maintain common infrastructure (e.g., ML library deployments, continuous integration, testing) and perform focused machine learning software development tasks across a variety of application domains. You will work on a multi-disciplinary team in an environment that focuses on problems of interest to LLNL and Department of Energy (DOE) programs. You will apply fundamental knowledge of software development and machine learning to contribute to multiple projects using creativity and imagination. This position will be in the Center for Applied Scientific Computing (CASC) division in the Computing Principal 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.

You will 

• Employ moderately complex software engineering methods using industry standard software development practices and modern programming languages and operating systems.
• Assist in modernizing and deploying machine learning libraries and workflows to utilize the latest high performance computing systems and/or cloud platforms.
• Help develop, test and/or apply machine learning algorithms and pipelines to scientific applications.
• Contribute to the fulfillment of technical projects and organizational objectives functioning as an effective team member on multi-disciplinary teams.
• Engage other developers frequently to share relevant knowledge, opinions, and recommendations.
• Perform other duties as assigned.

Additional Responsibilities at the SES.3 level

• Manage multiple advanced parallel tasks and priorities of customers and stakeholders, ensuring deadlines are met, while leveraging team member’s skills.
• Design, implement, deploy, and maintain software systems using object-oriented analysis, design, and programming techniques.
• Provide solutions to complex problems that require in-depth analysis of tangible and intangible factors.

• Ability to obtain and maintain a US DOE Q-level security clearance which requires U.S. Citizenship.
• Master’s degree in Computer Science, Computer Engineering or related field, or the equivalent combination of education and related experience.
• Proficiency in a modern programming language such as C++ or Python.
• Experience deploying machine learning pipelines in production.
• Experience developing software on Linux HPC clusters or similar environments.
• Ability to work with limited direction on technical tasks and develop technical solutions.
• Proficient verbal and written communication skills to collaborate effectively in a team environment, prepare written reports and present and explain technical information.
• Interpersonal skills necessary to interact with a diverse set of scientists, engineers and other technical and administrative staff in a collaborative, multidisciplinary team environment.

In Addition at the SES.3 level

• Significant experience in working with diverse teams to solve complex problems and deliver practical solutions.
• Advanced verbal and written communication skills necessary to interact with a multi-disciplinary research team, author technical and scientific reports and papers, and deliver scientific presentations.
• Comprehensive analytical and problem-solving skills necessary to craft creative solutions and solve complex problems.

Qualifications We Desire

• Experience developing and deploying containers to local and cloud environments.
• Experience with continuous integration, testing and automated workflows.
• Experience with build systems such as CMake and/or software packaging and deployment.

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

Position Information

This is a Flexible Term appointment, which is for a definite period not to exceed six years.  If final candidate is a Career Indefinite employee, Career Indefinite status may be maintained (should funding allow).

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
• Our core beliefs - visit https://www.llnl.gov/diversity/our-values 
• Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement

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. Also, all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship. 

Pre-Employment Drug Test

External applicant(s) selected for this position must 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.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. 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.

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

Reasonable Accommodation

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 use our online form to submit a request. 

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.