Machine Learning Software Developer
- Full-time
- Organization: Computing
- Category: Information Technology/Computing
- Job Code 2: SES.2 Science & Engineering MTS 2
- Employee Referral Bonus: $1500
- Job Code 1: SES.1 Science & Engineering MTS 1
- Pre-Employment Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
- Pre-Placement Medical Exam: Not applicable
- Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
- Position Type: Flexible Term
Company 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.
Job Description
We have an opening for a Machine Learning Software Developer to help to shape research and development efforts to derive greater knowledge from dense and sparse sensor networks operating across multiple phenomenological modalities. You will also contribute to the maturation of Large Language Model-driven agents, which work to augment the analytical capabilities of scientific staff working on this area. This position is programmatically in Global Security’s Nuclear Thread Reduction (N) Program and administratively in the Global Security Computing Applications Division (GS-CAD) within the Computing 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
- Contribute to the development of software applications using object-oriented analysis, design, and programming techniques in Python.
- Under general direction, provide computer science, machine learning, or software development support to multitalented teams using industry standard software development practices, modern programming languages, and operating systems.
- Contribute to the development of a range of Large Language Model (LLM) centric applications including scientific, graphical user interface, database, and visualization applications on Windows and/or UNIX platforms.
- Participate in the requirements definition, analysis, design, implementation, debugging, testing, and optimization of computer programs on workstations.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.2 level
- Work independently, under limited direction, in all phases of the software development lifecycle, including design, implementation, and deployment of new features within both existing and new applications.
- Provide solutions to broadly defined and moderately complex problems through independent analysis, practical problem-solving, and effective execution.
- Contribute to the design, implementation, and deployment, ensuring alignment with project requirements, technical standards, and operational goals.
Qualifications
- Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
- Bachelor's degree in computer science, machine learning, computer engineering, artificial intelligence or related technical field, or an equivalent combination of technical education and relevant experience.
- Fundamental knowledge with development of Reinforcement learning, LLM frameworks, agentic AI, or Graph Neural Networks.
- Familiar with the software development life cycle, including activities such as requirements gathering, preparing documentation, implementing features, and testing code.
- Familiar with developing software for High-Performance Computing (HPC) environments and interacting with HPC systems such as job scheduling tools like Flux or SLURM.
- Fundamental knowledge developing software with Python, C++ or JAVA within Linux, UNIX, and/or Windows environments.
- Sufficient verbal and written communication skills necessary to collaborate effectively in a team environment and present and explain technical information.
Additional qualifications at the SES.2 level
- Master’s degree in computer science, machine learning, computer engineering, artificial intelligence or related field, or an equivalent combination of technical education and relevant experience.
- Ability to effectively manage concurrent technical tasks with competing priorities, along with the demonstrated ability to effectively change focus when necessary.
- Proficient verbal and written communication skills to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-technical experts, and advise senior management and/or external sponsors, and interpersonal skills necessary to effectively collaborate in a team environment.
- Broad experience in and comprehensive knowledge of multi-modal data collection, agentic AI/ML, Model-Context-Protocol (MCP), or other LLM integrations
Qualifications We Desire
- PhD with significant focus in computer science, computer engineering, AI/ML, or a related technical field.
- Knowledge of one or more of the following computer science disciplines: embedded systems, scientific data analysis, machine learning, systems programming, software engineering, or high-performance computing.
- Previous experience working Department of Energy, Department of Homeland Security, Department of Defense, a utility, manufacturing, or a hardware/software company.
- Advanced verbal and written communication skills necessary to present technical information, provide technical guidance, and interact effectively with management and external sponsors.
Pay Range
$121,830 - $185,544 Annually
$121,830 - $154,500 Annually for the SES.1 level
$146,340 - $185,544 Annually for the SES.2 level
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
Additional Information
#LI-Onsite
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 2026 Best Places to Work by Glassdoor!
- Flexible Benefits Package
- 401(k)
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules (*depending on project needs)
- Our values - visit https://www.llnl.gov/inclusion/our-values
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.
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