Senior Machine Learning Engineer

Join NVIDIA in Santa Clara for an onsite Senior Machine Learning Engineer role that foregrounds what you gain: a competitive salary range of USD 184,000 to 356,500 per year, equity participation, and comprehensive benefits, all while collaborating across LiDAR and camera teams to advance autonomous driving. You will help build the ML backbone of the DRIVE AV perception stack, focusing on LiDAR and camera perception, data pipelines, and production-ready C++ code.

Responsibilities

• Design, train, and optimize ML models for LiDAR perception, including road element detection, semantic segmentation, and tracking.
• Build and coordinate end-to-end ML workflows, spanning data pipelines, model training, evaluation metrics, continuous performance instrumentation, and reporting.
• Productization: transition models from initial evaluation to shipped components within the DRIVE AV platform, delivering efficient production-grade C++ code.
• Innovation: stay current with ML advances and integrate techniques that boost platform performance.
• Collaborate with LiDAR and camera teams, developers, engineers, and managers to turn complex ideas into reliable autonomous driving solutions.

Requirements

• BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
• 6+ years of relevant proven industry experience applying machine learning to address real-world problems.
• Strong C++ and Python programming and debugging skills with experience in developing for large, complex systems.
• Deep practical experience applying ML to LiDAR/camera perception in automotive or related fields.
• Experience with deep learning frameworks such as PyTorch or TensorFlow and a solid understanding of ML mathematics.
• Building and sustaining training and essential metric workflows for large-scale datasets.
• Excellent communication and analytical skills, with a self-motivated drive to solve hard problems.

Technologies

• C++
• Python
• PyTorch
• TensorFlow
• TensorRT

Benefits

• Equity
• Benefits

Ways to Stand Out

• LiDAR or Camera Perception Experience: Proven track record of developing and shipping deep learning models for LiDAR/Camera in a production environment.
• Advanced Model Knowledge: Familiarity with modern network architectures like Transformers and their application to visual recognition tasks.
• AV Production Experience: A history of delivering ML features and models into a production autonomous vehicle stack or a related robotics product.
• Performance Optimization: Experience with model optimization for real-time inference on embedded or automotive platforms, such as TensorRT.