Back
Tier-1 brand, mid-level generalist ML role, and metro location increase applicant competition significantly.
Strong aerospace and flight-physics requirements make background fit highly domain-specific and less transferable.
Multiple mandatory filters (5+ years, flight physics expertise, supplier management, MLOps) make shortlisting highly strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Translate high-level aerospace business needs into AI technical requirements and develop validated machine learning prototypes.
Lead adoption of standardized MLOps and POD platforms to ensure technical consistency across Flight Physics organization.
Collaborate with domain experts on Verification & Validation strategy essential for certification and support aerodynamic engineering teams in industrial programs.
Master's degree in Aerospace Engineering, Mathematics, Data Science, Computer Science, or related field.
At least 5 years of professional experience in data science and AI, specifically in aerospace flight physics context.
Mandatory experience in aircraft design, characterization, and simulation within aerospace industry.
Supplier management experience is mandatory.
Deep technical expertise in advanced AI techniques (e.g., LLMs, CNNs) applied to aerospace flight physics challenges.
Experienced in prototyping high-impact AI solutions and preparing for industrialization with MLOps workflows.
Able to act as a specialist consultant within aerodynamics, loads, or mass domains to translate engineering needs into AI solutions.