Lead the architectural strategy, design, and execution of the end-to-end autonomous driving data engine for Bosch XC’s L2+ ADAS and autonomous driving stacks.
Compensation
The U.S. base salary range for this full-time position is $240,000 - $320,000.
Responsibilities
Define and execute the technical roadmap and strategy for the E2E Autonomous Driving Data Engine, including fleet data loop automation, active learning pipelines, auto-labeling, simulation, and MLOps tooling.
Oversee the end-to-end architecture, development, and testing of the AI data flywheel and its seamless interaction with edge fleet triggers, cloud data lakes, model repositories, and automotive target hardware.
Collaborate closely with cross-functional leads (data engineering, cloud infrastructure, embedded runtime SOC teams) to define, drive, and scale the integrated AI machinery ecosystem.
Establish a rapid-evaluation development framework that accelerates the benchmarking, active learning selection, and continuous integration of emerging multimodal E2E AI solutions.
Guide the transition of raw fleet log data and research prototypes into scalable, production-grade training and auto-labeling pipelines, ensuring runtime performance optimization on automotive-grade hardware.
Requirements
Master’s degree or Ph.D. in Computer Science, Robotics, Electrical Engineering, AI, or a closely related field focused on autonomous systems
Partner with cross‑functional teams to deliver AI‑powered products that transform customer interactions and build AI foundation models.
Locations (4)
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, United States
San Jose, California, United States
Compensation
The minimum and maximum full-time annual salaries for this role are listed below, by location. Cambridge, MA: $262,500 - $299,600; McLean, VA: $262,500 - $299,600; New York, NY: $286,400 - $326,800; San Jose, CA: $286,400 - $326,800
Responsibilities
Partner with data scientists, software engineers, ML engineers and product managers to deliver AI‑powered products
Running multi-GPU or multi-node training jobs on large-scale sensor datasets
Interacting with product and downstream deployment teams to identify perception bottlenecks and shape the roadmap for new capabilities
Requirements
MSc in computer science, machine learning, robotics, or a closely related field
Nice to have: PhD in computer vision, machine learning, robotics, or a related field
Partner with cross-functional teams of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products
Leverage technologies such as Pytorch, AWS Ultraclusters, Huggingface, Lightning to analyze large datasets
Build AI foundation models through design, training, evaluation, validation and implementation
Engage in high impact applied research to advance AI capabilities
Define and steward novel research directions
Requirements
PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields
M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields
Nice to have: PhD focus on NLP
Nice to have: Masters with 10 years of industrial NLP research experience
Staff AI Research Engineer - Computer VisionHelsing GmbH · Munich, Germany+3 more
Research Scientist Intern, Foundation Model Optimization (PhD)Meta · Bellevue, US