Staff Machine Learning Engineer, Motion Planning

At Woven by Toyota, a Staff Machine Learning Engineer focuses on developing and optimizing cutting-edge machine learning models for autonomous motion planning. This role involves rigorous research and development to advance the performance and reliability of models designed for integration into next-generation autonomous vehicles. The engineer will also collaborate with cross-functional teams to ensure that ML models are effectively deployed.

To be considered for the Staff Machine Learning Engineer position at Woven by Toyota, candidates should have a PhD or Master's in fields like Machine Learning, Robotics, or Computer Science, along with 8+ years of practical experience using ML frameworks like PyTorch or TensorFlow. A deep understanding of learning-based planning and proficiency in Python or C++ are also essential for this role.

Key skills for a Staff Machine Learning Engineer at Woven by Toyota include expertise in deep learning techniques, a solid understanding of complex modeling and planning algorithms, and proficiency in programming languages such as Python or C++. Additionally, experience with data processing, model training, and hands-on applications in autonomous driving technology are highly beneficial.

While not strictly required, having experience with autonomous systems is highly beneficial for the Staff Machine Learning Engineer role at Woven by Toyota. A background in related technologies like perception, prediction, mapping, and localization will enhance your ability to contribute effectively to projects aimed at advancing our autonomous vehicle technologies.

The working environment for a Staff Machine Learning Engineer at Woven by Toyota is collaborative and innovative, blending modern Silicon Valley creativity with traditional Japanese craftsmanship. Here, you’ll find a team dedicated to pushing the boundaries of mobility technology, in a setting that values diversity and promotes personal well-being.

When responding to this question, highlight your hands-on experience with popular frameworks such as PyTorch and TensorFlow. Discuss specific projects where you successfully implemented these frameworks, detailing the challenges you faced and how you overcame them. Always relate your experiences back to how they would enhance your contributions at Woven by Toyota.

Be prepared to discuss specific techniques you’ve used to enhance model performance, such as hyperparameter tuning, data augmentation, or architecture modifications. Providing concrete examples from your previous roles will demonstrate your analytical skills and hands-on expertise relevant to the Staff Machine Learning Engineer position.

When addressing this question, emphasize your experience working in collaborative environments. Describe how you communicate your technical insights to non-technical team members and seek input from various domains to enhance project outcomes, particularly within the context of motion planning and prediction systems at Woven by Toyota.

Explain imitation learning as a technique where models learn from demonstrations rather than explicit programming. Share an example where you applied imitation learning to build predictive models, focusing on the outcomes and insights you gained, which would be particularly interesting for your role at Woven by Toyota.

During your response, detail a specific project where you successfully deployed a machine learning model. Discuss the challenges faced during deployment and how you ensured the model’s performance and reliability in a production environment. Relating this experience to autonomous vehicle applications will be especially valuable.

Discuss various strategies for model evaluation such as cross-validation, performance metrics (accuracy, precision, recall) and real-world testing. Provide examples of how you've implemented these strategies in past projects to validate the practicality of your models, tying back to the rigorous evaluation needed for Woven by Toyota's applications.

Talk about the ways you stay informed, such as reading research papers, attending conferences, or participating in online courses. Highlight any recent advancements in ML that intrigue you and may be relevant to the autonomous motion planning field, reflecting your genuine passion for the industry.

Reflect on specific challenges you've faced in previous roles while working with autonomous systems. Discuss how you tackled these challenges, focusing on your problem-solving skills and innovative thinking, which are essential in the fast-evolving field at Woven by Toyota.

In your answer, elaborate on your familiarity with data processing techniques and the deep learning pipeline you’ve structured. Use past experiences to illustrate how you managed data at every stage—from initial cleaning to model training—and how this experience would directly apply to your role at Woven by Toyota.

Discuss your commitment to maintaining high coding standards through practices such as writing clean, documented code and participating in code reviews. Provide examples of how you’ve cultivated coding excellence in your previous roles, which will resonate with Woven by Toyota’s engineering culture.