Staff Deep Learning Engineer, State Estimation (R5785)

What you'll do

• Develop and evaluate models for visual correspondence, depth, pose estimation, and image-to-map localization, combining learned representations with geometric methods.
• Own data preparation, annotation and reproducible training workflows; evaluate performance, analyze failures, and improve models.
• Integrate learned measurements into navigation systems and support profiling, deployment, and delivery of tested Hivemind SDK components.

What they ask for

• M.S. in a related field and 4+ years of related professional experience, or Ph.D. and 2+ years.
• Hands-on experience designing, training, debugging, and evaluating deep-learning models using PyTorch or an equivalent framework.
• Strong foundations in camera models, coordinate transformations, projective geometry, and multi-view geometry, with practical experience in a related computer-vision field.
• Strong Python skills and experience taking computer-vision capabilities from raw data through training, evaluation, and integration readiness.

Nice to have

• Experience with aerial imagery, geospatial data, elevation maps, or cross-condition or cross-sensor matching.
• Experience with model export, quantization, TensorRT, ONNX, embedded deployment, or physical-platform validation.

Pay

USD 200,000–300,000 (per-year-salary) — base salary

Tools

PyTorch, Python, TensorRT, ONNX, VIO, SLAM, Structure from Motion (SfM)

AI focus

Develops and evaluates deep-learning models for visual navigation, localization, and geometric estimation, including data and training pipelines and deployment recommendations.