AI Researcher, Internship – PhD Student

General Motors

. Lead research and prototyping of advanced machine learning methods, including foundation models, vision-language architectures, diffusion models, image/video generation, self-supervised learning, imitation learning, and reinforcement learning .

Posted 11/9/2026part-timeHerzliya • IsraelEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in advanced machine learning methods, including deep learning architectures and reinforcement learning, with a strong foundation in Python and ML frameworks. Proven ability to collaborate across teams and contribute to innovative solutions in autonomous driving technologies.

Highest-signal resume keywords

Ph.D. In Machine LearningProficiency In PythonExperience With PyTorchExperience With TensorFlowResearch Experience In AI/ML

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine Learning TechniquesDeep Learning ArchitecturesReinforcement LearningGenerative ModelsMultimodal LearningAnalytical Problem SolvingLarge-Scale DatasetsHigh-Performance ComputingImage/Video GenerationSelf-Supervised Learning

Soft Skills

CollaborationSelf-Driven MotivationTechnical Communication

Tools & Technologies

ML FrameworksAutonomous VehiclesAdvanced Driver Assistance Systems

Industry Keywords

Foundation ModelsVision-Language ArchitecturesDiffusion ModelsAutonomous DrivingL3 Technologies

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Lead research and prototyping of advanced machine learning methods, including foundation models, vision-language architectures, diffusion models, image/video generation, self-supervised learning, imitation learning, and reinforcement learning
Prototype ML models that improve perception, prediction, or decision-making for autonomous driving
Collaborate with cross-functional teams including perception, robotics, and systems engineering
Participate in technical discussions, share insights, and work toward publishing results
Contribute to next-generation autonomous driving, L3, and beyond technologies

Requirements

What you’ll need

Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field
Able to work fulltime during the academic summer break
Solid understanding of modern machine learning techniques, especially deep learning architectures such as transformers, generative models, and multimodal learning
Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
Research experience in AI/ML demonstrated through coursework, academic projects, or publications
Intent to return to degree program after completion of the internship (preferred)
Familiarity with autonomous vehicles or advanced driver assistance systems (ADAS) (preferred)
Experience with large-scale datasets and training ML models in high-performance computing environments (preferred)
Proven track record of significant results demonstrated by grants, fellowships, patents, or first-authored publications at leading workshops or conferences (preferred)
Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches (preferred)
Experience building systems based on machine learning, reinforcement learning, and/or deep learning methods (preferred)

Benefits

Comp & perks

Mentorship from experienced AV researchers
Experience with real-world AI/ML systems
Collaboration with leading researchers and engineers
Opportunity to work toward publishing results
Inclusive workplace focused on belonging and employee development
Reasonable accommodations for applicants with disabilities