Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. 

The ML Platform team at Waymo provides a set of tools and technologies to support and automate the lifecycle of the machine learning workflow, including feature and experiment management, model development, debugging & evaluation, deployment, and monitoring. These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Behavior Prediction, Planner, Routing, Maps and Research, ensuring greater degrees of consistency and repeatability, and addressing the “last mile” of getting models into production and managing them once they are in place. We work hand in hand with machine learning experts in all parts of the company as well as our collaborators across Alphabet.

We are looking for engineers with a variety of backgrounds and are passionate about enabling ML to join our team. Current projects include:

• Collaborating with hardware architects, software engineers, and data scientists to take full advantage of Waymo’s hardware architecture as well as innovate to enable autonomous driving.
  
• Developing and maintaining a platform and ML libraries that enable a fast research to production lifecycle, including tools to support model evaluation, model debugging, hyperparameter tuning, benchmarking, and model optimization.
  
• Developing Waymo’s compiler powering inference of deep nets and compute workloads with an emphasis on performance.
  
• Developing benchmarking and profiling tools to optimize inference workloads and analyze performance behavior within the car.

At a minimum, we’d like you to have:

• B.Sc. in Computer Science, Mathematics, or a related field.
  
• Strong C++ and/or Python programming skills.
  
• 5+ years of experience developing large-scale distributed computing or data infrastructures.
  
• Experience with deep learning frameworks (e.g. TensorFlow, PyTorch, and Apache MXNet).
  

It’s preferred if you have one or more of the following:

• M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning.
• Experience with building infrastructure and tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization.
• Experience with the following technologies: XLA, TVM, MLIR, LLVM, deep learning models and algorithms, and deep learning framework design.
• Experience developing and deploying models for edge devices.
• Experience in compiler design for CPU and off-load engines such as GPU, NPU, and TPU.