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Strong Tier-1 brand and mid-level role increase competition, but aerospace specialization narrows qualified pool.
Role requires aerospace flight physics and certification-focused V&V, limiting cross-industry transferability.
Mandatory 5+ years, aerospace flight physics, supplier management, and specific ML/MLOps skills create strict filters.
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Lead rapid prototyping and development of advanced AI models (e.g., LLMs, CNNs, surrogate models) to address high-impact flight physics use cases.
Drive adoption of standardized MLOps and POD platforms to ensure technical consistency and support verification and validation for future certification.
Partner with domain experts to identify engineering pain points, build business cases, and translate needs into AI technical requirements while managing external supplier deliverables.
Master’s degree in Aerospace Engineering, Mathematics, Data Science, Computer Science, or related field.
Minimum 5 years professional experience in data science, including AI and big data analytics; plus 5+ years experience in aircraft design, characterization, or simulation required.
Mandatory knowledge of Flight Physics in aerospace context and mandatory supplier management experience.
Proficiency with Python and core data science tools; experience with cloud platforms, ETL pipelines, and experiment tracking systems; advanced English language skills required.
Experienced technical leader comfortable working at the intersection of AI/data science and aerospace engineering domains with hands-on prototyping and industrialization of AI solutions.
Strong operational executor who can build validated models, drive standardization, and collaborate effectively across distributed and cross-functional teams.
Strategic thinker skilled in consulting engineering teams, defining V&V strategies for certification, and managing external partners to deliver scalable AI infrastructure.