
Senior Machine Learning Engineer, Computer Vision
- Seattle, WA
- $150,000-200,000 per year
- Permanent
- Full-time
- Design and implement algorithms for multi-camera object detection, classification, and persistent tracking.
- Build scene understanding modules to extract landmarks, spatial layout, and semantic context from image streams.
- Develop cross-camera fusion and localization methods for consistent identification and positioning of objects.
- Architect and deploy visual search systems using vector databases (e.g., OpenSearch, FAISS, Milvus) for image-based retrieval and matching.
- Design and implement re-ranking techniques to improve retrieval precision based on context, metadata, and scene cues.
- Create tools and metrics to evaluate retrieval quality, localization accuracy, and perception robustness.
- Collaborate across ML, backend, and infrastructure teams to ensure scalable, real-time deployment.
- Investigate system-level issues, drive debugging efforts, and improve model and system performance.
- Mentor junior engineers and contribute to long-term vision for perception, localization, and image retrieval.
- M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field.
- 5+ years of industry experience in computer vision, image retrieval, or perception systems.
- Strong background in object detection, tracking, and scene understanding using multi-camera inputs.
- Deep understanding of vector-based retrieval systems and experience with OpenSearch, FAISS, or similar tools.
- Proficiency in Python or C++, with hands-on experience in PyTorch, TensorFlow, and OpenCV.
- Experience in building large-scale image retrieval pipelines, including feature extraction, indexing, and search optimization.
- Knowledge of multi-view geometry, and cross-camera identity association.
- Experience evaluating and tuning re-ranking strategies using contextual and multi-modal signals.
- Exposure to cloud-based deployment of search systems (e.g., OpenSearch cluster tuning, sharding, replication).
- Experience with edge deployment of perception pipelines (e.g., Jetson, Qualcomm).
- Publications or patents in the fields of visual search, localization, or multi-camera perception.