Top Tech Jobs & Startup Jobs

Develop and train deep learning models for autonomous-driving perception, including object detection, scene understanding, and 3D perception. Design and analyze pipelines from data through deployment, collaborate with algorithm, software, and data teams, and research computer vision and multi-task learning methods for production-ready models.

Integrate and maintain embedded application software and algorithm libraries for internal and customer-facing releases. Manage Git and GitLab integration branches, coordinate cross-team integration tasks, validate versions, resolve code conflicts, and assign issues. Perform hands-on debugging and testing while overseeing release and feature management across multiple projects. Maintain Linux-based software versions and support CI systems to improve testing coverage.

Integrate embedded application software and algorithm libraries for internal and customer-facing releases. Responsibilities include maintaining Linux software versions, managing Git/GitLab integration branches, coordinating cross-team integration, validating versions, resolving code conflicts, debugging and testing components, and managing releases, features, and CI testing coverage.

Integrate and maintain embedded application software and algorithm libraries for internal and customer-facing releases. Manage Git and GitLab integration branches, coordinate cross-team integration tasks, validate software versions, resolve code conflicts, debug and test components, and manage releases, features, and CI testing coverage across multiple projects.

Lead SOTIF analysis for autonomous vehicle systems by developing safety KPIs, requirements, guidelines, methods, and tools. Collaborate with R&D, validation teams, customers, regulators, and automotive stakeholders to identify and mitigate safety risks, validate system behavior, and promote industry acceptance of Mobileye’s SOTIF methodology.

Implement, maintain, and refactor C++ software; integrate algorithmic modules with platform and vehicle systems; coordinate APIs and interfaces; troubleshoot bugs, integration issues, CI/CD pipelines, and system bottlenecks; maintain technical documentation and improve AI-assisted development workflows.

Design, build, and optimize production-grade automotive imaging radar software. Implement complex DSP algorithms on multi-core, distributed-memory platforms; plan memory, data transfer, computation pipelines, and core utilization for resource-constrained environments. Collaborate with research teams and contribute to innovative autonomous-driving sensor technology.

Develop state-of-the-art deep learning, computer vision, and geometric modeling algorithms for lane detection, ADAS, and autonomous driving. Responsibilities include research, prototyping, deployment on real-time embedded vehicle systems, dataset analysis, and collaboration with engineering and research teams to improve algorithm performance and robustness.

Develop road perception models and algorithms using vision, maps, and multi-sensor data. Own end-to-end road data pipelines across cloud and on-premises environments, perform geometric reasoning from 2D images to 3D world space, implement algorithms for autonomous vehicle production systems, and build evaluation tools, metrics, and supporting infrastructure.

Develop and maintain computer-vision and signal-processing algorithms for autonomous driving. Implement features and production-ready code in C++ and Python/NumPy, transition research into product, collaborate with cross-functional teams, and solve complex real-world problems.