Top Tech Jobs & Startup Jobs

The Staff AI Engineer will build and deploy AI/ML solutions for simulations, working with teams to evaluate and implement AI tools. Responsibilities include leading projects, fine-tuning models, and optimizing performance across various applications in engineering.

The role involves optimizing large-scale ML infrastructure for autonomous vehicles, conducting analyses, collaborating with teams, and improving system performance.

Technical lead for vehicle dynamics, planning, and controls within Embodied AI. Define technical vision, architect systems, lead design and validation, mentor engineers, and drive safety-critical autonomy software from design through on-road validation.

Senior individual contributor designing and deploying onboard ML solutions for autonomous driving. Develop models (detection, tracking, trajectory, safe AI), build training pipelines and deployment tooling, translate research into production, collaborate cross-functionally, and mentor engineers.

Lead design and delivery of production-grade AI capabilities to improve developer productivity across engineering tools, CI/CD, and embedded software workflows. Define technical vision, integrate AI into toolchains, drive productionization, establish responsible AI standards, mentor engineers, and influence cross-functional roadmaps and implementations.

Design, implement, and deploy ML models for autonomous driving (detection, tracking, trajectory generation). Apply advanced techniques (imitation learning, RL, foundation models), collaborate cross-functionally, and support production ML systems and model deployment.

Hands-on technical leader for embedded chassis controls software: deliver C/C++ real-time control software, build tools and CI/CD, drive architecture and test strategies, mentor engineers, improve developer workflows, and lead cross-team process and automation improvements to raise software quality and productivity.

Manage day-to-day semiconductor suppliers to ensure supply continuity, negotiate commercial terms, monitor performance, resolve issues, build dashboards and reports, partner cross-functionally, and drive supplier performance and risk mitigation.

Lead and grow a cloud platform engineering team building event messaging, data, and storage services across Azure and GCP. Drive delivery, operational excellence, monitoring/observability, incident response, backlog and program management, and developer enablement for shared platform services. Partner with stakeholders to define roadmap and improve reliability, security, scalability, and developer experience.