Sr. Robotics Engineer - Perception and AI
Tasks
- Analyze perception requirements
- Build field data observability loops
- Calibrate and debug sensor fusion
- Collaborate with hardware cloud and software teams
- Collect and curate datasets
- Deploy models to edge
- Design perception pipeline architecture end to end
- Develop data engine pipeline
- Develop event logic for perception
- Evaluate pipeline performance
- Fuse RGBD camera and LiDAR and IMU data
- Generate synthetic data from simulation
- Implement OTA model updates
- Implement auto labeling
- Maintain IoT and fleet data pipelines
- Mentor engineers on perception and ML
- Perform closed loop evaluation
- Select classical computer vision or foundation model approach
- Train machine learning models
- Verify system performance with test automation
Perks/Benefits
- N/A
Skills/Tech-stack
3D Geometry | AWS | Active Learning | Auto-labeling | Azure | C++ | CUDA | Camera Calibration | Closed Loop | Closed Loop Evaluation | Controls and dynamics | Data labeling | Deterministic systems | Diffusion Models | Diffusion Policy | Distillation | Docker | Edge Computing | Fine Tuning | Foundation Models | GCP | Git | IMU | Imitation Learning | IoT pipelines | Kalman Filter | Lidar | Linux | Mqtt | Multi-Modal | Multi-Modal Learning | ONNX | ONNX optimization | Open Vocabulary | OpenCV | Path Planning | PyTorch | Python | Quantization | RGBD | ROS 2 | Real Time | Real-time Systems | SLAM | Sensor fusion | Shell Scripting | Simulation | State Estimation | Synthetic data | Tensor calibration | TensorRT | TensorRT Quantization | Time Systems | VLA | VLA fine tuning | VLA models | Vision foundation models
Education
Roles
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