Top Tech Jobs & Startup Jobs

Design and deploy machine learning models for creating HD maps, utilizing advanced ML techniques and collaborating with other teams to deliver reliable solutions.

Lead programmatic media buying and ad ops across DSPs and Google/Apple channels, build in-house programmatic capabilities, deploy AI-driven automation, negotiate PMP/PG deals, and partner with analytics to measure incrementality and feed MMM.

Lead development of vehicle platform concepts and layouts for autonomous and TaaS vehicles. Collaborate with Product, Systems, Design, and OEM partners using 3D CAD to resolve subsystem conflicts, set package targets, and present concepts to executive leadership and external partners.

Design and specify microarchitectures and high-performance execution units for ML accelerators. Translate researcher requirements into hardware features, optimize power/area/performance, and collaborate with verification teams to ensure functional correctness and performance.

Define and document human factors, occupant packaging, and comfort requirements for AV platforms. Benchmark competitors, develop occupant layouts with Product and Design, build and test ergo bucks and mockups, run user clinics, and integrate ergonomics and regulatory standards into vehicle designs while negotiating targets with OEMs and suppliers.

The Executive Business Partner supports the CEO with strategic management, coordinates complex scheduling, enhances operational excellence, and builds cross-functional relationships.

As a Staff Machine Learning Engineer, you will enhance AV simulations using foundation models, lead experiments, develop realism metrics, and manage teams.

Lead end-to-end ML model development for safety-critical driving behaviors, design experiments, improve data quality, deploy models and metrics fleet-wide, and communicate results across product and engineering teams.

As a Senior Machine Learning Engineer, you will develop ultra-realistic simulations for autonomous vehicles using foundation models, collaborate with teams, design experiments, and integrate models into applications.

Improve distributed input data pipelines for large-scale ML training workloads, collaborating with researchers to enhance data processing systems and implement advanced ML infrastructure tools.