Senior/Staff Machine Learning Engineer - Offline Driving Intelligence

In this role, you will:

• Lead Technical Initiatives: You will apply modern machine learning, leveraging large-scale data, to critical validation problems at the intersection of ML and data science. You will serve as a key contributor and tech lead on a small, focused team.
• Improve Model Interpretability: You'll pioneer methods to understand the internal workings of our machine learning models. This work will be crucial for building trust and ensuring the safety of our autonomous systems.
• Improve Feature Representation: You'll extend and refine the features and embedding space used by our models to better identify and cluster interesting driving scenarios. This involves leveraging a deep understanding of the autonomous driving stack and applying first-principles thinking to derive new, impactful features.
• Integrate AV Performance Data: You'll incorporate metrics and information on autonomous vehicle (AV) performance into the model to make its risk predictions more accurate and relevant.
• Collaborate Cross-Functionally: You'll work closely with system safety, data science, software, and fleet operations teams to understand their needs and integrate improvements that directly support our validation efforts.

Qualifications

• Experience: A PhD in a relevant field and/or 5+ years of experience working with machine learning models and data science methodologies in an industry setting.
• Technical Skills: Expertise in machine learning concepts, including training deep learning models, evaluation, and optimization. Strong programming skills in Python and experience with relevant machine learning libraries (e.g., PyTorch, TensorFlow, Jax). Experience with large-scale data processing and distributed computing.
• Domain Knowledge: Experience in robotics, autonomous vehicles, or a related field, with an understanding of challenges in perception, prediction, and planning.
• Mindset: Proven ability to drive progress independently, lead technical projects, and apply critical thinking to solve practical problems.
• Communication: Excellent communication skills and the ability to work effectively with cross-functional teams.

Bonus Qualifications

• Real-world impact as demonstrated in publications, patents, presentations, blog posts, etc. 
• Familiarity with encoder-decoder or foundation models for prediction and planning.
• Experience with test scripting and data analysis languages like SQL.
• Experience with techniques for machine learning model interpretability and explainability.
• Familiarity with the challenges of fleet data collection and validation in the autonomous vehicle space.