🚗 Woven by Toyota: Enabling Toyota's Mobility Transformation 🚗
Woven by Toyota is at the forefront of Toyota's century-defining transformation into a mobility company. Inspired by a legacy of innovation for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation. We aim to expand the very definition of "mobility" and how it serves society.
Our work is structured around four key pillars:
- AD/ADAS: Our autonomous driving and advanced driver-assist technologies.
- Arene: Our software development platform for software-defined vehicles.
- Woven City: A dedicated testbed for mobility innovations.
- Cloud & AI: The digital infrastructure powering our collaborative foundation.
Business-critical functions empower these teams to execute their vision. Together, we are united by a bold goal: a world with zero accidents and enhanced well-being for all.
🌟 TEAM: Autonomy at the Intersection of AI, Robotics, and Advanced Driving 🌟
At Woven by Toyota, we tackle the complex challenges of Autonomy, merging AI, Robotics, and Advanced Driving. Our work encompasses a diverse range of activities, from analyzing petabytes of multimodal driving data and solving optimization problems in computer vision, to minimizing latency on hardware accelerators. We are dedicated to deploying scalable and efficient machine learning (ML) training and evaluation pipelines, and designing novel neural network architectures to advance the state-of-the-art in ML for Perception, Prediction, and Motion Planning. We are actively seeking doers and creative problem solvers to join us in improving mobility for everyone with human-centered automated driving solutions for both personal and commercial applications.
The Behavior team is responsible for building the machine learning training and deployment ecosystem for AD/ADAS. You will be an integral part of the Automated and Assisted Driving team, collaborating closely with Autonomy ML engineers focused on Perception and Planning. Our mission is to design scalable, reliable, and cost-effective ML infrastructure that facilitates rapid iteration and deployment of high-quality ML models. This includes everything from large-scale data curation and distributed training to push-button deployment in production environments.
🎯 Who We Are Looking For 🎯
We are seeking motivated software interns with a strong interest in ML systems and MLOps. The ideal candidate possesses hands-on experience training machine learning models and is eager to contribute to improving the infrastructure that supports ML research and production at scale.
This role is perfectly suited for individuals who thrive at the intersection of software engineering and machine learning. Interns in this position will contribute to well-scoped infrastructure projects and play a key role in identifying and addressing bottlenecks within dataset creation, distributed training, and model evaluation pipelines.
This position offers invaluable opportunities for close collaboration with senior engineers and ML practitioners, regular technical feedback, and the chance to influence core platform components that are utilized daily by AD/ADAS ML engineers. Successful candidates will gain exposure to production-grade ML infrastructure and make measurable improvements to the reliability, scalability, and efficiency of the ML development lifecycle.
🚀 RESPONSIBILITIES 🚀
- Own and drive well-defined projects within our ML platform and training infrastructure.
- Analyze performance, scalability, and reliability bottlenecks in production ML workflows.
- Improve observability of training and evaluation pipelines through profiling, logging, and telemetry.
- Design and integrate MLOps tools that enhance developer productivity and system reliability.
- Develop robust integration tests to improve platform stability.
- Quantify and validate improvements through systematic benchmarking and experimentation.
- Document technical designs and findings, and present progress and results to the team.
📚 MINIMUM QUALIFICATIONS 📚
- Currently pursuing a BSc, Master’s, or PhD in Computer Science, Computer Engineering, or a related field.
- Expert proficiency in Python and experience with PyTorch or similar ML frameworks.
- Experience with containerization and deployment technologies (e.g., Docker).
- Experience building scalable data processing or ML workflows using systems such as Kubernetes, Airflow, Flyte, or similar platforms.
- Experience designing, implementing, and maintaining software systems or research tooling.
- Proficiency with version control systems (e.g., Git).
- Familiarity with benchmarking, experimentation, and performance evaluation methodologies.
💡 NICE TO HAVES 💡
- Experience with distributed training frameworks (e.g., PyTorch Distributed, Horovod).
- Knowledge of cloud infrastructure and resource management (e.g., AWS, GCP, Azure).
- Experience designing ML systems or infrastructure for research or production environments.
- Background in autonomous driving, robotics, or large-scale perception systems.
- Familiarity with C++ or performance-critical systems programming.
- Strong technical writing and presentation skills.
🤝 Our Commitment 🤝
- We are an equal opportunity employer and value diversity.
- Any information we receive from you will be used solely in the hiring and onboarding process. Please see our privacy notice for more details.