Top Tech Jobs & Startup Jobs

The QA Engineer will design and execute testing plans for autonomous driving software, analyze test scenarios, and document outcomes. Collaboration with cross-functional teams is crucial for improving test processes and safety metrics.

Build ETL pipelines that transform vehicle, API, database, sensor, logistics, and testing data into reliable warehouse datasets. Write optimized SQL, create Grafana dashboards, collaborate with teams to deliver required data, and explore AI and LLM tools for analysis automation. The role requires Python data-library expertise, advanced SQL, modern pipeline development, BI-tool experience, workflow orchestration familiarity, and strong data quality ownership.

Support the Head of Delivery Sales in expanding Avride’s delivery robot service across U.S. university campuses. Responsibilities include developing go-to-market strategies, generating and closing business opportunities, managing the education sales pipeline, building campus partnerships, conducting market research, preparing proposals, tracking performance, and monitoring industry trends. The role requires strong communication, organization, analytical ability, and willingness to travel 25%.

Own autonomous-vehicle safety testing across QA gates, acceptance criteria, reporting, release decisions, and evidence generation. Define and calibrate safety thresholds, classify findings, connect hazard analyses to scenario coverage, coach QA engineers, validate metrics, translate safety frameworks into testable requirements, and track applicable regulations. The role requires influencing cross-functional teams, documenting residual risk clearly, and supporting safety cases and regulatory readiness.

Owns quality acceptance and release qualification for analytical metrics used in autonomous-driving software decisions. Responsibilities include defining comprehensive case spaces, identifying silent failures, reviewing implementations, creating test data, building regression tests, quantifying defects, and communicating evidence-based fixes. The role requires strong Python and SQL, statistical literacy, product judgment, and experience testing data-heavy systems. Autonomous vehicles, robotics, ML evaluation, ClickHouse, A/B testing, and annotation experience are preferred.

Develop and maintain CI/CD pipelines, hardware-in-the-loop systems, firmware deployment tools, diagnostics, and embedded-system testing infrastructure. Collaborate with hardware and software teams on system architecture, monitor infrastructure performance, resolve firmware development issues, and improve build, test, and deployment workflows for autonomous vehicles and robots.

Lead ML infrastructure engineer owning GPU inference performance for onboard real-time and high-throughput offboard systems. Improve and maintain C++ inference framework, optimize GPU execution, collaborate with applied ML teams, and expand ownership across ML pipelines and distributed infrastructure.

The Machine Learning Engineer will develop and optimize models, manage datasets, enhance training pipelines, and collaborate across teams to innovate in autonomous vehicle technology.

Develop and maintain the software framework for autonomous vehicle autopilot systems, focusing on performance, safety, and reliability, while implementing automated testing processes.

Develops motion planning algorithms, collaborates with engineering teams, and optimizes performance for autonomous vehicle decision-making.