Top Tech Jobs & Startup Jobs in Boston, MA

Develop and integrate motion-planning and decision-making algorithms for autonomous driving. Build robust, scalable C++ code and CI/CD pipelines, process and analyze vehicle field data, optimize large data pipelines, lead feature development, and mentor junior engineers.

The Senior Technical Program Manager will oversee software performance evaluations, manage resources, and coordinate between engineering teams to ensure quality metrics are met while addressing risks and issues.

Lead the development of the ML Data Service platform, manage engineers, drive technical strategy, and ensure high-quality data for ML use cases.

Lead multiple machine learning teams focusing on prediction and planning for autonomous vehicles, setting technical direction, and fostering organizational growth through innovative AI solutions.

As a Machine Learning Systems Engineer, you will optimize distributed training systems, enhance performance profiling, and develop high-performance GPUs for machine learning workloads.

Lead the research and development of algorithms for motion planning in autonomous driving, integrating predictive systems and mentoring team members.

Lead development of rigorous evaluation frameworks and statistical methods to measure and validate autonomous vehicle system performance. Monitor metric reliability, detect drift, identify edge cases, correlate simulation and on-road results, and feed scenarios into simulation catalogs. Partner with safety, systems, and engineering teams to inform launch decisions, build self-service tooling for developers, and mentor peers. Introduce scalable ML methods where appropriate to improve evaluation rigor and coverage.

The Staff Motion Planning Engineer will lead the research and development of algorithms for motion planning in autonomous vehicles, ensuring robust software integration and mentoring team members.

Lead technical roadmap and architecture for ML data infrastructure supporting petabyte-scale pipelines. Manage and mentor engineering team, design ingestion/transformation/serving systems, ensure data quality, lineage, governance, and collaborate with ML and infrastructure teams to deliver production-grade ML data pipelines and feature stores.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.