Duties and Responsibilities
- Develop deep learning models for a variety of autonomy applications (relevant areas: object detection, classification, segmentation, behavior prediction, end-to-end driving).
- Research, design, improve, and implement state-of-the-art ML algorithms and deploy them onto self-driving vehicles and in datacenters.
- Identify or collect the required datasets and implement data processing pipelines.
- Deliver reliable software through continuous integration, automated testing, and code reviews.
- Address the real-world issues encountered during tests or customer deployments.
Qualification and Experience
- Bachelor’s Degree in Computer Science, Mechanical Engineering, Electrical Engineering, or equivalent. Advanced Degrees highly preferred.
- Demonstrated ML Engineering experience developing either Computer Vision models (preferred) or other models (such as LLMs, Finance, Ads, or others).
- Production experience with Deep Learning models (training, fine-tuning, or deployment).
- Excellent software engineering skills in Python or C++.
- Strong analytical skills in linear algebra, geometry, and probability.
- Experience with a deep learning framework, such as PyTorch, JAX, TensorFlow.
Extra Credit
- Relevant industry experience with low-latency systems (prior work on self-driving vehicles, autonomy, and/or robotics projects).
- Experience building models from sensor data: lidar, radar, camera.
- Experience with multi-modal models.
- Strong academic track record in any field related to machine learning, as evidenced by top-tier publications.
- Production ML experience with either: Model conversion and optimization for production (ONNX, TensorRT); Model deployment on specialized hardware (e.g. Jetson).
- Ability to lead the ML area as the team grows (for Sr Staff level candidates)
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