Lead the ML infrastructure layer with focus on optimizing GPU inference performance for real-time onboard and high-throughput offboard autonomous driving applications. Requires deep experience with PyTorch, C++, GPUs, distributed systems, and performance optimization.
Lead Software Engineer architecting and implementing Model Predictive Control (MPC) systems and vehicle dynamics models for autonomous vehicles. 80% hands-on C++ development and optimization with 20% technical leadership and mentoring of a small controls team. Requires 6+ years experience, deep MPC/optimization expertise, and strong individual contribution.
Develops and deploys deep learning models for autonomous vehicles and robots, managing datasets, training pipelines, and inference optimization. Requires 4+ years ML experience, expertise in PyTorch/TensorFlow, and advanced degree in CS/ML/Robotics.
Builds and scales ML compute platform on Kubernetes with Argo Workflows and Ray for distributed training, orchestration, and resource governance. Optimizes performance, debugs issues, and integrates tooling for ML teams at scale. Requires deep Kubernetes, systems, and programming expertise.
Develops and deploys deep learning models for motion planning and behavioral prediction in autonomous vehicles using petabytes of driving data. Requires strong Python, PyTorch/TensorFlow expertise, full ML lifecycle experience, and C++ for real-time inference.
Develops, optimizes, and deploys deep learning models for autonomous vehicles and robots, managing large datasets and training pipelines. Requires 3+ years experience with PyTorch/TensorFlow, Python, and expertise in computer vision or LLMs.
Lead the ML infrastructure layer with focus on optimizing GPU inference performance for real-time onboard and high-throughput offboard autonomous driving applications. Requires deep experience with PyTorch, C++, GPUs, distributed systems, and performance optimization.
Lead Software Engineer architecting and implementing Model Predictive Control (MPC) systems and vehicle dynamics models for autonomous vehicles. 80% hands-on C++ development and optimization with 20% technical leadership and mentoring of a small controls team. Requires 6+ years experience, deep MPC/optimization expertise, and strong individual contribution.
Develops and deploys deep learning models for autonomous vehicles and robots, managing datasets, training pipelines, and inference optimization. Requires 4+ years ML experience, expertise in PyTorch/TensorFlow, and advanced degree in CS/ML/Robotics.
Builds and scales ML compute platform on Kubernetes with Argo Workflows and Ray for distributed training, orchestration, and resource governance. Optimizes performance, debugs issues, and integrates tooling for ML teams at scale. Requires deep Kubernetes, systems, and programming expertise.
Develops and deploys deep learning models for motion planning and behavioral prediction in autonomous vehicles using petabytes of driving data. Requires strong Python, PyTorch/TensorFlow expertise, full ML lifecycle experience, and C++ for real-time inference.
Develops, optimizes, and deploys deep learning models for autonomous vehicles and robots, managing large datasets and training pipelines. Requires 3+ years experience with PyTorch/TensorFlow, Python, and expertise in computer vision or LLMs.