Top AI & Machine Learning Jobs

The Senior Manager of Embodied AI will oversee AI/ML engineering teams, manage operational excellence in data scaling for autonomous vehicles, and collaborate across teams to improve performance and innovation in AV technology.

Lead a team developing AI/ML solutions for vehicle motion control and estimation. Oversee design, implementation, and deployment of embedded AI systems, mentor engineers, coordinate cross-functional teams, ensure project delivery using agile practices, and drive adoption of AI/ML across the organization.

Design, prototype, and productionize applied AI/ML solutions for simulation and engineering workflows. Build high-performance inference pipelines, fine-tune and optimize multimodal and 3D models, integrate models into simulation or perception stacks, and lead projects end-to-end while collaborating with simulation, data, and engineering teams.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

Lead the design and implementation of advanced ML models for autonomous driving, collaborating with teams, mentoring engineers, and driving technical initiatives.

As an AI/ML Engineer, develop and optimize analytics frameworks to enhance autonomous vehicle development, focusing on automation tools and collaboration with engineering teams.

The AI/ML Data Scientist will develop and deliver innovative AI/ML solutions, train models, collaborate with business partners, and communicate findings effectively.

Lead end-to-end ML projects for automotive manufacturing: design, train, validate, deploy, and monitor models; implement MLOps/CI-CD; perform data engineering, EDA, and model evaluation; ensure data security and regulatory compliance; document and communicate results to stakeholders.

The Principal AI/ML Engineer will lead the AV ML Infra team, overseeing scalable ML infrastructure, project ownership, collaboration, and team mentorship in AI and ML innovation at GM.

As an ML Infrastructure Engineer, design backend components, enhance platform performance, and drive system improvements while collaborating across teams.