Software Engineering Manager - AI Data Engine
$172,000–$229,000 year
Remote · United States or Boston, Massachusetts, United States
Job Summary
Lead and grow Motional’s Data Stack as a Software Engineering Manager for the AI Data Engine. Define and execute the technical vision for storing metrics and generating ML datasets for large computer vision and behavioral models, accelerate data loaders, ingestion, and querying across petabyte-scale datasets, and collaborate with ML research/training and data engineering teams. Manage, mentor, and develop a high-performing team of data and infrastructure engineers, align team goals with company objectives, and drive cross-functional initiatives. Ideal candidate has 8+ years in data platform engineering, 3+ years in technical lead/management with 3-7 direct reports, experience with data warehouses or lakehouse architectures, and strong skills in Python, AWS/GCP, Parquet/Iceberg/Lance, and orchestration frameworks (Airflow/Step Functions). Bonus points for autonomous-vehicle domain experience and Bazel. The role supports a hybrid schedule with in-office time in Boston, Pittsburgh, or Las Vegas, or can be fully remote in the U.S. Salary range $172k–$229k base, with potential bonuses/equity; benefits include medical, dental, vision, 401k, HSA, life/pet insurance, and more.
Required Qualifications
- BS or MS in Computer Science or related field
- 8+ years of professional experience in data platform engineering
- 3+ years of experience in a technical lead or management role with 3-7 direct reports
- Extensive experience with managing large (petabyte plus) scale data platforms such as data warehouses, object storage, and ML training data stores
- Extensive experience with workflow orchestration frameworks such as Airflow or Step Functions
- Strong programming skills in Python
- C++ experience is a plus
- Deep knowledge of data storage formats such as Parquet, Iceberg, and Lance
- Strong knowledge of cloud infrastructure (AWS, GCP)
- Prior experience with building data warehouses or lakehouse architectures in ML or robotics contexts
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