Senior Data Engineer
@ Toyota Research InstituteSenior Data Engineer
This job is still taking applications, but it's been up a while.
About the job
Toyota Research Institute (TRI) develops AI, robotics, and materials sciences to improve human life, focusing on autonomous driving and mobility innovations.
Requirements
- 8+ years of data software experience
- Proficient in Python, SQL
- Experience with ETL frameworks
- Knowledge of cloud architectures
- Familiar with sensor data formats
Qualifications
- Bachelor’s or Master’s in related field
- Experience in robotics or autonomous systems
- Strong software engineering fundamentals
- Experience with high-volume data systems
Full job description
At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.
Responsibilities
- Design and implement scalable, production-grade pipelines for data ingestion, transformation, storage, and retrieval from vehicle fleets and simulation environments.
- Build internal tools and services for data labeling, curation, indexing, and cataloging across large and diverse datasets.
- Collaborate with ML researchers, autonomy engineers, and data scientists to design schemas and APIs that power model training, evaluation, and debugging.
- Develop and maintain feature stores, metadata systems, and versioning infrastructure for structured and unstructured data.
- Support the generation and integration of synthetic datasets with real-world logs to enable hybrid training and simulation workflows.
- Optimize pipelines for cost, latency, and traceability, ensuring reproducibility and consistency across environments.
- Partner with simulation and cloud platform teams to automate workflows for closed-loop testing, scenario mining, and performance analytics.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- 8+ years of experience building data-intensive software systems, ideally in robotics, autonomous driving, or large-scale ML environments.
- Proficient in Python, SQL, and familiar with C++.
- Experience designing ETL pipelines using modern frameworks (e.g., Apache Spark, Flyte, Union).
- Strong knowledge of cloud-native architectures, including AWS services (e.g., S3, or equivalents (Google Cloud platform)
- Familiarity with sensor data types (camera, lidar, radar, GPS/IMU) and common data serialization formats (e.g., protobuf. ROS2bag, MCAP).
- Deep understanding of data quality, observability, and lineage in high-volume systems.
- Track record of building reliable and performant infrastructure that supports both ad-hoc exploration and repeatable production workflows.
Bonus Qualifications
- Experience in AD/ADAS, robotics, or autonomous systems — especially handling perception or planning datasets.
- Familiarity with ML pipeline orchestration frameworks (e.g. Kubeflow, SageMaker, etc).
- Experience working with temporal or spatial data, including geospatial indexing and time-series alignment.
- Exposure to synthetic data generation, simulation logging, or scenario replay pipelines.
- Strong software engineering fundamentals, CI/CD, testing, code review, and service deployment best practices.
- Experience collaborating with cross-functional, distributed teams across research and production orgs.
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