Guidance, Navigation & Control (GNC)/Flight… at LLNL · Livermore

companyDescription 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. jobDescription We have multiple openings for a Guidance, Navigation, & Control (GNC)/Flight Dynamics Software Developer in support of the Flight Performance Integration (FPI) program. FPI supports LLNL weapon system design and assessments with modeling and simulation utilizing custom in-house computational codes. You will perform code development work focused on a Python modeling environment (library) to generate an integrated tool to interface with multiple engineering solvers and post-processing applications. This will involve developing methods and tools to streamline the engineering workflow, facilitate automation, and provide drop-in automated data extraction. This work prepares for a planned AI driven virtual design assistant. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate. Depending on your assignment, these positions may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. These positions will be filled at either level based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level. You will Contribute to the development of new aerospace engineering analysis capabilities, such as optimal control, advanced 3DoF trajectory optimization, 6DoF trajectory optimization, and autopilot design software. Support concept trade studies and derive GN&C requirements for future systems utilizing in-house flight simulation tools and engagement modeling codes such as AFSIM. Contribute to the development of tools for managing CFD, Trajectory, Finite Element Analysis (FEA) and other numerical modeling workflows including preprocessing, post-processing, and data management. Perform analysis of with a variety of flight modeling related tools with an emphasis on assembling them to enable novel analysis at scale utilizing high-performance computing (HPC) resources. Support engineering and flight modeling analysts including debugging problems, providing alternative solutions, and quick feature implementation. Document methods and implementation in both informal and formal reports and presentations. Share relevant knowledge, analysis, and recommendations in collaboration with internal and external scientists, engineers, mathematicians, and computer scientists through reviews and working groups. Collaborate with other development teams working on tools that support analysis workflows. Perform other duties as assigned. Additional job responsibilities at the SES.3 level Independently determine technical objectives and criteria to satisfy project deliverables and execute the appropriate technical approaches. Apply advanced technical knowledge and best practices to guide successful completion of project and organizational goals. Lead and mentor junior staff, student fellows, and summer student researchers. qualifications Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. Citizenship. Master’s degree in engineering, computational science, applied math, physics, or related field, or the equivalent combination of education and related experience. Demonstrated programming ability in Python, C, C++, FORTRAN, or similar languages. Proficient understanding of computational vehicle dynamics via 3-DoF and/or 6-DoF flight/reentry modeling including familiarity with aerodynamic performance coefficients. Proficiency in vector calculus, linear algebra, and numerical methods for solving differential equations (ODEs/DAEs). Knowledge of trajectory optimization tools and methods such as GPOPS-II, Dymos, OTIS, TAOS, STK, or similar. Knowledge of dynamic optimization methods such as direct collocation, shooting methods, nonlinear programming, sequential quadratic programming, algorithmic differentiation, and related tools such as CasADI, Pyomo, IPOPT, & SNOPT. Proficient interpersonal, written, and verbal communication skills necessary to effectively present and explain technical information. Ability to work in a multidisciplinary team environment, as well as independently. Ability to travel. Additional qualifications at the SES.3 level Advanced knowledge and significant experience in computational modeling & Multi-disciplinary Design and Analysis Optimization (MDAO), including significant experience in developing modeling & simulation tools for aerospace applications. Significant experience with one or more programming languages such as Python, C/C++, FORTRAN, or other object oriented programming (OOP) languages. Advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management. Qualifications We Desire PhD in engineering, computational science, applied math, physics, or related field. Experience conducting computational analysis in a multi-physics context and with software on massively parallel systems, particularly in the areas of heat transfer, fluid dynamics, and/or structural mechanics. Experience in development of software in a version-controlled environment (e.g. git), including testing, documentation, and software user support. Experience with machine learning frameworks (e.g. torch/pytorch, tensorflow, jax) and models, as well as training and fine-tuning models and one or more of the following: non-linear programming and optimization, uncertainty quantification, Bayesian learning, UI/UX design. Pay Range $146,340 - $222,564 $146,340 - $185,544 Annually for the SES.2 level $175,530 - $222,564 Annually for the SES.3 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. additionalInformation #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 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. 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. 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