Senior/Staff Engineer, Machine Learning - Online Mapping
Develop and productize online mapping models for autonomous navigation using real-world sensor data. The role requires deep ML expertise, robotics or computer vision experience, strong Python and deep learning framework skills, and a staff-level ability to deliver practical solutions.
About the job
Responsibilities
- Research, develop, and implement state-of-the-art online mapping models and algorithms.
- Analyze and characterize online mapping system performance, identifying improvements to architecture, data, and evaluation in an end-to-end ML system.
- Collaborate cross-functionally with ML teams to integrate models into centralized architectures.
- Partner with autonomy, infrastructure, and systems stakeholders on online mapping needs and requirements.
Requirements
- Proven experience solving in-production ML problems and balancing data, model, and evaluation tradeoffs.
- Deep understanding of ML fundamentals and hands-on experience training and evaluating modern ML models in autonomous vehicles, robotics, mapping, computer vision, or related fields.
- Experience with robotics-related ML applications and 3D geometry.
- Strong Python skills and experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Ability to make practical, data-driven decisions and deliver solutions on schedule.
Nice-to-haves
- Experience working with complex, multi-component systems.
- Experience building ML pipelines and optimizing or productizing ML models.
- Familiarity with distributed training and ML compilers.
- Research publications in conferences such as NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, or ICRA.
- Deep understanding of 3D geometry and state estimation fundamentals.
Compensation
- Base pay range: $193,930–$291,150.
- Eligible for an annual performance bonus, equity, and benefits.
Skills
Machine Learning, Online Mapping, Python, PyTorch, TensorFlow, JAX, Computer Vision, Robotics, 3D Geometry, State Estimation, Ml Pipelines, Distributed Training, Ml Compilers, Lidar
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