Senior Machine Learning Engineer bei Woven-by-toyota

TeamAt Woven by Toyota, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep learning and optimization, particularly in complex 3D geometric computer vision scenarios. We're seeking passionate innovators and creative problem-solvers eager to redefine mobility through cutting-edge AI and robotics, contributing directly to shaping the future of self-driving technology.Woven by Toyota is developing a joint project between Toyota Research Institute (TRI) and Woven by Toyota to research and develop a fully end-to-end learned automated driving / ADAS stack. This cross-org collaborative project is synergistic with TRI’s robotics division’s efforts in Diffusion Policy and Large Behavior Models (LBM).

Responsibilities

Own design and development of ML models or model components for end-to-end autonomous driving: ranging from initial data strategy, design, development, experimentation, evaluation and deployment.

Resolve ambiguities and address uncertainties arising from complex projects involving multiple teams and legacy codebases.

Enable and help other colleagues on the team to be more effective through leading by example when it comes to writing high-quality code, being rigorous with Machine Learning experimentation and knowledge sharing.

Collaborate closely with stakeholders from multiple teams in different time-zones to define interfaces and requirements for an end-to-end stack.

Experience

MS, or higher degree, in related field, or equivalent industry experience

Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred)

Knowledge of debugging and profiling deep neural networks on NVIDIA CUDA stack

Experience in state of the art architectures for object detection and 3D perception

Experience in ML workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization

Python and C++ experience

Hands-on experience with building a perception stack for autonomous systems

Familiarity with recent breakthroughs in ML (e.g. foundation models, pre-training and efficient fine-tuning, multimodal Transformer architectures) 

Hands-on experience with large scale distributed training

Nice to Have

Hands-on experience with building a perception stack for autonomous systems

Experience with model deployment with NVIDIA stack (e.g. ONNX graphs, TensorRT, profiling)

Experience with PyTorch and Computer Vision for sensor fusion (e.g. BEV representations)

Experience with embedded ML platforms and real-time OSes

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