Toyota’s Manufacturing Data & Tech Enablement team is on a mission to modernize and optimize our production systems through advanced analytics and AI-driven innovation.
Requirements
- 3+ years working as a Machine Learning Engineer or equivalent experience
- 3+ years experience with big data platforms and Industrial IOT time-series data
- 3-5+ years experience with cloud data platforms like AWS, Azure, or GCP to leverage cloud-based data storage and processing capabilities
- 3-5+ years experience with both relational (RDBMS) and non-relational (NoSQL) databases
Responsibilities
- Developing End-to-End ML Pipeline design, build, and deploy robust ML models from data ingestion to production deployment, ensuring automation, scalability, and maintainability
- Implement MLOps best practices including CI/CD for ML, monitoring, retraining pipelines, and model governance
- Building experimental prototypes to test different machine learning approaches and validate concepts before full implementation
- Working closely with data scientists, business analysts, and manufacturing SMEs to understand project requirements, interpret results, and communicate insights effectively
- Applying software engineering principles like version control, code review, and modular design to ensure the maintainability and scalability of machine learning systems
- Staying current with AI/ML advancements, particularly in manufacturing and industrial IoT domains
Other
- To save time applying, Toyota does not offer sponsorship of job applicants for employment-based visas or any other work authorization for this position currently.
- The ideal candidate thrives at the intersection of manufacturing operations and cutting-edge AI, is capable of working autonomously, and is passionate about deploying scalable, maintainable, and production-ready ML solutions in a fast-paced, data-rich environment.
- Ability to collaborate with data scientists, analysts, and other stakeholders to understand their data needs and translate them into technical solutions
- A work environment built on teamwork, flexibility, and respect
- Professional growth and development programs to help advance your career, as well as tuition reimbursement
