AI and Computer Vision Engineer

Responsibilities

Our client, a confidential aerospace organization, needs an experienced AI and Computer Vision Engineer to build perception systems for autonomous spacecraft operations. You will design and train deep-learning models that estimate relative position and orientation from camera imagery, working with synthetic and laboratory data optimized for flight-ready hardware.

Your day-to-day responsibilities include:

• Designing, training, and evaluating deep-learning models for 6-DoF pose estimation of spacecraft
• Owning the complete training pipeline: dataset generation, augmentation, domain adaptation across synthetic and real imagery, experiment tracking, and reproducibility
• Optimizing models for embedded compute through knowledge distillation, pruning, quantization, and quantization-aware training while benchmarking latency, memory, and power constraints
• Porting and evaluating models on embedded and neuromorphic hardware, characterizing accuracy versus energy trade-offs
• Building explainability and uncertainty measures into the pipeline to debug failure modes and support certification readiness
• Exploring privacy-preserving and distributed training approaches for collaborative model improvement
• Prototyping self-supervised refinement methods for in-flight model adaptation
• Defining requirements, test scenarios, and validation criteria with guidance and navigation teams
• Running validation campaigns on hardware-in-the-loop testbeds and analyzing performance
• Managing training compute resources efficiently across cloud GPU and internal infrastructure

What We're Looking For

Education: MSc or PhD in computer science, electrical engineering, robotics, aerospace, physics, or a related field with strong machine learning focus.

Experience: 3+ years building and deploying deep-learning computer vision systems (object detection, keypoint detection, pose estimation, or 3D perception). PhD research in the field counts toward this requirement.

Required Skills:

• Demonstrable experience taking models from prototype to constrained deployment: quantization, distillation, latency optimization, and embedded or accelerator hardware deployment
• Experience training on synthetic data and bridging the sim-to-real gap
• Hands-on laboratory work: camera systems, calibration, test setup, data collection and annotation
• Strong Python and PyTorch (or JAX/TensorFlow) with clean, version-controlled, reproducible code
• Solid classical computer vision and 3D geometry: camera models, intrinsics/extrinsics, distortion, PnP, RANSAC, coordinate frames
• Comfortable with Linux, Git, containers, and running large training jobs on GPU clusters or cloud platforms
• Self-directed and hands-on: you will own your work with review support rather than daily oversight
• Clear technical communication in reports and reviews
• Working proficiency in English; German is a plus

Nice to Have:

• Familiarity with spacecraft navigation or vision-based systems
• Spiking neural networks, neuromorphic hardware, or event-based cameras
• Federated learning, differential privacy, or secure aggregation
• Rendering and synthetic data generation tools
• Experience with space or safety-critical software assurance

How We Work With You

We are representing our client in this search. Interested candidates apply directly through Get A Job.ai. Our talent team will conduct an initial screening to assess fit, then submit qualified candidates to the client for consideration. Please do not contact the client directly—all communication flows through our recruiting process to ensure the best experience for everyone involved.

Pay

Compensation details will be discussed during the screening process based on experience and qualifications.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome candidates of all backgrounds and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, or disability status.