🚗 Woven by Toyota: Empowering the Future of Mobility 🚗
Woven by Toyota is at the forefront of Toyota's century-defining transformation into a mobility company. Driven by a legacy of innovation for the betterment of society, our mission is to redefine mobility through human-centric innovation, expanding its scope and societal impact.
Our work is structured around four key pillars:
- AD/ADAS: Developing cutting-edge autonomous driving and advanced driver-assist technologies.
- Arene: Building a robust software development platform for software-defined vehicles.
- Woven City: Creating a real-world testbed for mobility innovations.
- Cloud & AI: Establishing the digital infrastructure that powers our collaborative efforts.
Business-critical functions support these teams, all united by a singular, ambitious goal: a world free from accidents and enhanced well-being for everyone.
🤖 The Team: Driving Autonomy Forward 🤖
At Woven by Toyota, we confront the complexities of Autonomy at the confluence of AI, Robotics, and Advanced Driving. Our endeavors encompass a wide spectrum of challenges, including:
- Analyzing vast quantities of multimodal driving data.
- Solving intricate optimization problems in computer vision.
- Minimizing latency on hardware accelerators.
- Deploying scalable and efficient machine learning (ML) training and evaluation pipelines.
- Designing novel neural network architectures to push the boundaries of ML for Perception, Prediction, and Motion Planning.
We are actively seeking proactive and imaginative problem-solvers to join us in enhancing mobility for all through human-centered automated driving solutions for both personal and commercial applications.
The Behavior team is dedicated to building the ML 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 engineer scalable, reliable, and cost-effective ML infrastructure that facilitates rapid iteration and deployment of high-quality ML models, from large-scale data curation and distributed training to seamless push-button deployment in production.
🌟 Who We Are Looking For 🌟
We are searching for enthusiastic software interns with a profound interest in ML systems and MLOps. The ideal candidate will possess practical experience in training machine learning models and a keen desire to enhance the infrastructure that underpins ML research and production at scale.
This role is perfectly suited for individuals eager to work at the intersection of software engineering and machine learning. Interns in this position will contribute to well-defined infrastructure projects and play a vital role in identifying and resolving bottlenecks within dataset creation, distributed training, and model evaluation pipelines.
This internship offers close collaboration with senior engineers and ML practitioners, consistent technical feedback, and the opportunity to influence core platform components utilized daily by AD/ADAS ML engineers. Successful candidates will gain invaluable exposure to production-grade ML infrastructure and contribute to measurable improvements in the reliability, scalability, and efficiency of the ML development lifecycle.
🚀 Responsibilities 🚀
- Lead and drive well-defined projects within our ML platform and training infrastructure.
- Analyze performance, scalability, and reliability bottlenecks in production ML workflows.
- Enhance the observability of training and evaluation pipelines through profiling, logging, and telemetry.
- Design and integrate MLOps tools that boost developer productivity and system reliability.
- Develop robust integration tests to bolster 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.