Mechanical Engineer II- #26-22739

US Tech SolutionsSeattle, WA

About The Position

Seeking an Aerospace Engineer to act as a domain expert supporting AI Research initiatives. This role bridges traditional aerospace engineering and artificial intelligence by helping the team develop, validate, and stress-test AI tools tailored for aerospace systems, flight dynamics, and structural analysis. The engineer will partner closely with AI researchers to evaluate engineering workflows, define benchmarks, and ensure AI outputs meet the rigorous standards of the discipline.

Requirements

  • Power-user proficiency with industry-standard aerospace design and simulation tools (e.g., STK, NASTRAN/PATRAN, ANSYS Fluent, OpenVSP, or MATLAB/Simulink).
  • Broad foundational knowledge across aerospace sub-fields (aerodynamics, propulsion, orbital mechanics, avionics).
  • Experience working in cross-functional environments and communicating technical engineering information clearly to non-domain audiences (e.g., software engineers, AI scientists).
  • Ability to manage multiple tasks and meet deadlines in a fast-paced environment.
  • Basic scripting skills (e.g., Python, MATLAB) to help parse data or interface with AI environments.
  • 3-5 years of practical, post-graduation aerospace engineering experience.
  • Bachelor’s degree in Aerospace Engineering or related engineering field, or equivalent practical experience.

Nice To Haves

  • Advanced software engineering or machine learning expertise is not required.

Responsibilities

  • Evaluate the feasibility, safety, and practical utility of AI-generated aerospace designs, mission profiles, and complex simulations.
  • Help design, collect, and validate specific engineering tasks, edge cases, and evaluation metrics (validators) that AI models need to master.
  • Operate comfortably across a wide range of aerospace sub-disciplines, applying generalist knowledge in aerodynamics, propulsion, orbital mechanics, and avionics (GNC) to assess model performance.
  • Partner directly with AI researchers and cross-functional stakeholders to translate complex aerospace constraints into clear, actionable feedback for model training.
  • Ensure all evaluated deliverables and AI-generated outputs follow applicable aerospace engineering standards, safety requirements, and documented processes.
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