Materials Data Engineer – Active Clearance Required

We are seeking a Materials Data Engineer to join our team. In this role, you will work under the guidance of principle investigators to design data and analysis pipelines to support the Laboratory's AI-initiatives. This includes but not limited to sparse datasets, manufacturing, and high-throughput experimentation. As part of the Materials Engineering Division (MED) within the Engineering Directorate, you will contribute to advancing strategies for national security and support DOE’s Genesis Mission. This position provides an excellent opportunity to work at the forefront of science, automation, and machine learning.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week. 

You will

• Design and implement data processing and analysis pipelines that are scalable and AI-ready for high-throughput laboratory experimental systems to support end-to-end and hardware-software workflows and interface with enterprise data lake platforms such as MongoDB.
• Develop, deploy, and maintain application‑layer and AI‑assisted control software that interfaces with industrial and laboratory hardware — including PLCs, robotic controllers, motion systems, sensors/actuators, machine vision systems, and HMI/SCADA platforms — to provide robust, low‑latency monitoring and control of experiments.
• Leverage AI and statistical methods to enable early detection of off‑normal or unsafe conditions, scaling from benchtop experiments to large integrated facilities and HPC platforms.
• Specify, integrate, and validate hardware–software safety and interlock functions in close collaboration with scientists, engineers, and technicians. Ensure that control logic, AI‑assisted decision components, data models, test plans, and configuration‑managed documentation meet LLNL, DOE, and applicable SIL/compliance, software quality assurance (SQA), and cyber‑security requirements while supporting rigorous change control and regression testing over the system life cycle.
• Participate in hardware design reviews and create reports.
• Perform other duties as assigned.

• This position requires an active Department of Energy (DOE) Q-level clearance or active Top-Secret clearance issued by another U.S. government agency at the time of hire.
• Bachelor's degree in computer engineering, Electrical Engineering, Mechatronics, or a related technical field, or equivalent combination of education and relevant experience.
• Experience developing software for data acquisition and processing, which includes tabular and time series data, and ingestion into databases such as MongoDB.
• Fundamental understanding of networking and IoT communication for remote monitoring and control, including designing secure, low latency networks that connect PLCs, robots, sensors, edge devices, and database backed services using protocols such as TCP/IP and RESTful APIs.
• Ability to work both independently and collaboratively in a multidisciplinary and dynamic team environment, utilizing experience and fundamental knowledge of experimental design, techniques, and execution.
• Sufficient organizational, verbal, and written communication skills to effectively collaborate in a team environment and present and explain technical information to a variety of audiences.
• Demonstrated experience designing and implementing safety-critical control systems (safety relays for laser systems, EMO circuits, door interlocks, remote interlock I/O, watchdog timers, and PLC‑based Safety Instrumented Systems) and standards-compliant architectures for high-energy or laser systems.

Qualifications We Desire

• Advanced degree in Computer Engineering, Electrical Engineering, Mechatronics, or a related technical field.
• Proficiency in computational data analysis and scientific programming, including experience applying Python stacks (NumPy, Pandas, matplotlib, ML frameworks, MongoDB, and automated CSV/Parquet pipelines) and schema/ontology design and visualization dashboards.
• Hands-on experience developing and tuning closed-loop control systems (e.g., PID) in PLCs, embedded firmware, or software, with additional skills in C/C++, LabVIEW, MATLAB, and collaborative development tools (e.g., Git).

Pay Range

$121,830 - $154,500 Annually

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting.  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.

#LI-Hybrid

Position Information

This is a Career Indefinite position, open to Lab employees and external candidates.

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 an active Department of Energy (DOE) Q-level clearance or active Top Secret clearance issued by another U.S. government agency at time of hire. 

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.

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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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