Machine Learning Engineer
Job Description
Toyota Research Institute (TRI) is seeking a Machine Learning Engineer to join their Automated Driving Advanced Development division. This role is crucial in bridging TRI research with Toyota products through a collaborative project with Woven by Toyota, focusing on developing a fully end-to-end learned driving stack. The position offers an exciting opportunity to work at the intersection of machine learning, systems engineering, and real-world deployment.
The role involves implementing ML models for autonomous driving, from perception to trajectory planning, while ensuring robust deployment and testing. You'll work with cutting-edge technology in autonomous vehicles, collaborating with researchers and engineers across different specialties. The position requires strong expertise in ML frameworks, programming skills, and experience with real-world sensor data.
TRI offers a competitive compensation package, including a salary range of $176,000-$264,000 for California-based roles, comprehensive benefits, and an annual bonus structure. The company values diversity and inclusion, fostering an innovative and collaborative environment. This is an excellent opportunity for someone passionate about advancing autonomous driving technology while working for a leading research institution that's part of Toyota's global AI efforts.
The role combines practical ML engineering with real-world impact, offering the chance to work on complex autonomous systems while contributing to Toyota's vision of improving human life through technology. You'll be part of a world-class team working on transformative mobility solutions, with access to advanced resources and the opportunity to influence the future of autonomous driving.
Responsibilities For Machine Learning Engineer
- Implement, maintain, and evaluate end-to-end ML models used in the autonomy stack
- Collaborate with ML researchers, data scientists and engineers, and simulation teams to build training, evaluation, and deployment pipelines
- Integrate models into real-time systems running on simulation and vehicle platforms
- Support open-loop, closed-loop, and batch evaluation workflows of trained models
- Help design scalable workflows for managing large datasets
- Write clean, modular, well-tested code
Requirements For Machine Learning Engineer
- Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or related field
- 3+ years of strong experience with ML frameworks such as PyTorch, Tensorflow or Caffe
- Strong Python and C++ programming skills
- Familiarity with metrics dashboards, experiment tracking, and ML ops tooling
- Experience working with robotics or real-world sensor data
- Strong understanding of version control, testing, and software engineering fundamentals
- Enthusiasm for collaborative engineering and building reliable ML systems
Benefits For Machine Learning Engineer
- Annual cash bonus
- Vacation time
- Sick time
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