Rivet is seeking to advance its computer vision and sensor fusion capabilities for industrial workforces and defense personnel by developing integrated task systems that combine hardware, software, sensors, AI, and networking.
Requirements
- Proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow)
- Experience with ML pipeline development, model deployment, and production monitoring
- Knowledge of quantization, pruning, and edge deployment techniques
- Experience with computational photography, video processing, or camera systems
- Research background in multi-sensor data fusion, tracking, or SLAM
- Experience optimizing ML models for mobile/embedded deployment
- Knowledge of CUDA programming and GPU optimization
Responsibilities
- Implement POCs in Python/C++ to validate ML ideas on embedded hardware
- Conduct research in imaging and video processing pipelines for AR/VR applications
- Document learnings and define clear pathways from prototype to production
- Research and implement model optimization techniques for edge deployment
- Stay current with latest developments in computer vision and machine learning literature
- Prototype novel algorithms and validate performance through experimentation
- Design and implement end-to-end machine learning pipelines using PyTorch and TensorFlow Lite
Other
- BS with 5+ years of academic or industry experience in machine learning research or applied ML engineering with shipped or published work (or MS with 2+ yrs of the above)
- PhD in Computer Vision, Machine Learning, or related field (preferred)
- Publications in top-tier conferences (CVPR, ICCV, ECCV, NeurIPS, ICML) (preferred)
- Experience with AR/VR or mobile computer vision applications (preferred)
- Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines (preferred)
