About this position
ARCTOS Technology Solutions, LLCarctos-us.com/careers/ OVERVIEWReach New Heights! ARCTOS Technology Solutions, LLC (ARCTOS) is a fast-growing, technology-oriented small business providing aerospace, defense, and digital solutions, with offices and work sites across the United States. We’re looking for team-oriented innovators eager to tackle interesting challenges, work on important problems, and receive great benefits and employee support. REQUIREMENTARCTOS is seeking a highly skilled and motivated Research Engineer to join our team supporting AFRL’s Manufacturing Technology Division (AFRL/RXM). This role is focused on advancing the state-of-the-art in autonomous design and thermomechanical modeling for aerospace systems and integrating these models with cutting-edge additive manufacturing (AM) processes. The successful candidate will drive both fundamental and applied research, developing novel design and performance modeling frameworks that explicitly incorporate manufacturability constraints, specifically for AM technologies.PRIMARY RESPONSIBILITIESThe Research Engineer will work with Government customers, other ARCTOS personnel, and other Government organizations and contractors in the performance of the following duties:
- Design for Additive Manufacturing (DfAM):Research and develop methodologies for tailoring design and optimization frameworks (e.g., topology optimization, generative design) to account for AM process-induced constraints, defects, and material anisotropy.Integrate manufacturability metrics directly into the design loop to ensure optimized components are successfully produced using AM.
- The well-qualified candidate will have expertise in many of these areas:Common commercial simulation software and programming languages for custom tool development.Hands-on experience in tailoring and optimizing engineering design frameworks (e.g., optimization algorithms, surrogate modeling, machine learning).Proven experience in thermomechanical modeling for design, performance prediction, and manufacturing process modeling.Demonstrated experience with FEA and multi-physics applications.Experience with applying classic and modern machine learning algorithms to optimization and engineering problems, e.g. active learning (Bayesian optimization, reinforcement learning), deep learning (neural networks)Specific experience with additive manufacturing processes (e.g., Powder Bed Fusion, Directed Energy Deposition) and understanding of how process parameters influence material properties and component performance.
- M.S. or Ph.D. in Mechanical Engineering, Aerospace Engineering, Materials Science, or a closely related field.U.S. Citizenship is required
Salary Information
$93500.0 - $104100.0
Annual Salary