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General Motors avtomobil muhandisligi, ishlab chiqarish, transport va axborot texnologiyalari yo‘nalishlarida faoliyat yurituvchi global avtomobilsozlik va ishlab chiqarish kompaniyasidir. 1908-yilda tashkil etilgan GM nol darajadagi avariyalar, nol chiqindilar va nol tirbandlik haqidagi qarashlarini amalga oshirish bilan birga, harakatlanish imkoniyatlarini rivojlantirishga qaratilgan texnologiyalarni ishlab chiqadi. Kompaniyaning xalqaro faoliyati innovatsiyalar, barqaror transport va avtomobilsozlik sanoatining kelajagiga e’tibor qaratadigan yirik, ko‘p yo‘nalishli jamoalarni birlashtiradi.
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.
Tavsif
- 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
Talablar
- 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
Imtiyozlar
- 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
O‘xshash ish o‘rinlari
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