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Vakances uzņēmumā

PhD AI and Machine Learning Engineer Intern – Autonomous Vehicle Simulation at General Motors

PhD intern role at General Motors focused on researching and validating machine-learning models for autonomous vehicles. The work covers simulation, data systems, and evaluation tools supporting production-oriented AV capabilities.

USAmerikas Savienotās ValstisCAKalifornija
12 300 $ – 14 600 $ / mēnesis
HibrīdiPrakseSākuma līmenisNepieciešamā Valoda: angļuMašīnmācīšanās inženieris
C++PythonPyTorchTensorFlow

Apraksts

  • Develop and prototype advanced machine-learning approaches for perception, prediction, planning, and decision-making
  • Create, train, assess, and refine models with large-scale multimodal driving and sensor datasets
  • Develop data pipelines, experiment workflows, and evaluation tools that support rapid model iteration
  • Test models through simulation and other validation methods, including performance analysis and failure investigation
  • Improve models and systems for scalability, latency, reliability, and deployment requirements
  • Work with research and engineering teams to incorporate prototypes into autonomous-vehicle systems
  • Record research findings, communicate technical conclusions, and support publications or other research deliverables

Prasības

  • Be enrolled full-time in a PhD program in computer science, machine learning, artificial intelligence, robotics, engineering, or a related STEM discipline
  • Have at least one academic quarter or semester remaining after the internship ends
  • Show substantial AI and machine-learning research experience through publications, research projects, advanced coursework, or comparable technical work
  • Demonstrate a strong command of current machine-learning and deep-learning techniques
  • Program proficiently in Python and have practical experience with PyTorch, TensorFlow, JAX, or a comparable machine-learning framework
  • Know how to design experiments, interpret results, and apply quantitative problem-solving techniques
  • Bring solid programming, debugging, and software-development fundamentals
  • Communicate effectively and collaborate across research and engineering teams
  • Be available to work 40 hours per week throughout the internship
  • Preferred: research experience in autonomous vehicles, ADAS, robotics, computer vision, or embodied AI
  • Preferred: familiarity with foundation models, transformers, generative or diffusion models, or vision-language architectures
  • Preferred: experience with multimodal camera, lidar, radar, or other sensor data
  • Preferred: experience with self-supervised, imitation, reinforcement, or deep-reinforcement learning
  • Preferred: experience in distributed, parallel, or high-performance computing environments
  • Preferred: background in ML systems, data pipelines, experimentation frameworks, or production-focused model infrastructure
  • Preferred: experience with simulation, closed-loop environments, or validation against real-world driving scenarios
  • Preferred: knowledge of trajectory prediction, behavior planning, motion planning, perception, mapping, or structured scene understanding
  • Preferred: proficiency in C++ or another systems programming language
  • Preferred: experience with GPU programming, CUDA, accelerator frameworks, or performance profiling
  • Preferred: knowledge of numerical optimization, statistical estimation, probabilistic modeling, and systems-level tradeoff analysis
  • Preferred: first-author publications, grants, fellowships, patents, or open-source contributions

Priekšrocības

  • Paid holidays observed by GM in the United States
  • Access to GM’s Family First Vehicle Discount Program
  • Potential for growth within GM based on results
  • Internship events offering networking opportunities with company leaders and fellow interns
  • A one-time taxable lump-sum stipend for eligible students to help support relocation

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