
Senior Machine Learning Engineer, Perception β Autonomous Driving
Posted 1 day ago

Posted 1 day ago
This is a fully remote position, open to applicants in California, +4 more states.
β’ Create, train, and enhance machine learning models for LiDAR/camera perception and multi-sensor integration.
β’ Design and manage ML workflows that encompass data pipelines, model training, performance metrics, continuous performance monitoring, and reporting.
β’ Transform ML models and algorithms from evaluation and testing stages to deployment on the NVIDIA DRIVE AV platform.
β’ Write highly efficient product code utilizing C++.
β’ Stay updated on advancements in machine learning and integrate techniques to enhance platform performance.
β’ Work collaboratively with LiDAR/camera teams, developers, engineers, and managers to provide dependable autonomous driving solutions.
β’ MS or PhD in Computer Science, Engineering, or a related discipline, or equivalent professional experience.
β’ Over 8 years of demonstrated industry experience in utilizing machine learning to solve practical challenges.
β’ Proficient in C++ and Python programming and debugging, with a background in developing for large, intricate systems.
β’ Extensive hands-on experience in applying machine learning to LiDAR/camera perception and multi-sensor fusion within the automotive or similar sectors.
β’ Familiarity with deep learning frameworks like PyTorch or TensorFlow.
β’ Solid grasp of the mathematical principles underlying machine learning.
β’ Experience in establishing and maintaining training and essential metric workflows for extensive datasets.
β’ Exceptional communication and analytical abilities.
β’ A self-driven motivation to tackle challenging problems.
β’ Knowledge of contemporary network architectures such as Transformers.
β’ Experience in integrating ML features and models into a production autonomous vehicle stack or related robotics products.
β’ Background in optimizing models for real-time inference on embedded or automotive systems, including the use of TensorRT.
β’ Equity
β’ Benefits
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