描述
About the role:
As a Simulation AI/ML Engineer intern, you’ll partner with senior engineers to deliver key components of the evaluation strategy for GM’s autonomous vehicle programs. In this role, you will scale the testing and evaluation of our self-driving stack by applying AI/ML techniques to software solutions. You will design, perform experiments, and deploy these solutions as production-ready code. The work you do will be directly applied to the iteration and validation of the self-driving stack.
About the team:
The GM AV Simulation team builds world-class testing and analysis related products and technologies to enable GM to accelerate the development of autonomous vehicles as well as general vehicle software development. Our customers range from AV developers understanding the effects of their code on vehicle behavior, data engineers using our data pipelines to generate meaningful insights for various evaluation needs, to the release team tracking top-line performance metrics on releases. AV Simulation aims to deliver intuitive user experiences for robotics and AI engineers that accelerate GM towards a driverless future.
What you’ll do:
- Leverage AI/ML techniques to scale testing, classify autonomy performance, and mine critical scenarios, integrating human-in-the-loop where appropriate.
- Collaborate with engineers to integrate ML models into simulation tests and evaluation pipelines.
- Ramp up quickly on the codebase and domain; deliver assigned tasks efficiently with few iterations.
- Develop, test, and deploy production-ready code across components of our simulation infrastructure.
- Define problem statements and implement optimal, tradeoff-aware solutions that cover edge cases.
- Collaborate with cross-functional stakeholders, contribute to design and code reviews, and ensure seamless integration through clear communication.
Required Qualifications:
- Currently pursuing a Bachelor's Degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
- Must have at least one additional quarter/semester of school remaining following the completion of the internship
- Solid understanding of modern machine learning techniques
- Demonstrated coursework, research, or projects in AI/ML.
- Strong programming skills in Python.
- Able to work full-time, 40 hours per week.
Preferred Qualifications:
- Candidates are not expected to meet every qualification listed below. Depending on the needs of a specific Autonomous Vehicles team, a combination of these skills and areas of knowledge may be relevant.
- Currently pursuing a master's degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
- Exposure to deep learning architectures such as Transformers, CNNs, or diffusion models.
- Hands-on experience with one or more machine learning frameworks, such as PyTorch, TensorFlow, JAX, or Keras.
- Background in robotics and computer vision gained through projects or research.
- Familiarity with multimodal learning or working with sensor data.
- Interest in contributing to publications, open-source projects, or patents.
- Knowledge of systems programming languages, such as C++ or Java, is a plus.
- Intent to return to a degree program after completing the internship.
Compensation :
The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
- The salary range for this role is $8,100-$9,600 per month. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
- GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program - to help facilitate administration of relocation benefits, please apply using the permanent address you would move from.
What you’ll get from us (Benefits):
- Paid US GM Holidays
- GM Family First Vehicle Discount Program
- Result-based potential for growth within GM
- Intern events to network with company leaders and peers
Work Arrangement:
- Start dates for this internship role are May 24th and June 14th of 2027.
- Assignments will be based on team placement to ensure interns are located with their working team and leader.
- Hybrid : This role is categorized as hybrid. This means the successful candidate is expected to report to their designated work location three times per week, at minimum.
Renseignements sur la diversité
General Motors est résolue à être un lieu de travail qui est non seulement exempt de discrimination illégale, mais aussi un endroit qui favorise véritablement l'inclusion et l'appartenance. Nous sommes convaincus que la diversité de la main-d'œuvre permet de créer un environnement dans lequel nos employés peuvent s'épanouir et développer de meilleurs produits pour nos clients. Nous encourageons les candidats intéressés à consulter les principales responsabilités et compétences requises pour chaque rôle et à postuler à tout poste qui leur correspond. Dans le cadre du processus de recrutement, les candidats peuvent devoir, le cas échéant, réussir une évaluation liée au poste ou une présélection d'emploi avant d'être embauchés. Pour en savoir plus, consultez notre processus de recrutement.
Déclaration concernant l'égalité d'accès à l'emploi (É.-U.)
General Motors est fière d'être un employeur souscrivant au principe de l'égalité d'accès à l'emploi. Tous les candidats qualifiés seront pris en compte, sans égard à la race, à la couleur, à la religion, au sexe, à l'orientation sexuelle, à l'identité de genre, à l'origine ethnique, aux situations de handicap ou au statut protégé d'ancien combattant.
Aménagements (É.-U. et Canada)
General Motors offre des occasions à tous les chercheurs d'emploi, y compris les personnes handicapées. Si vous avez besoin d'un accommodement raisonnable pour vous aider dans votre recherche d'emploi ou la soumission de votre candidature, envoyez-nous un courriel à l'adresse [email protected] ou appelez-nous au 800 865-7580. Veuillez inclure dans votre courriel une description spécifique du type d'accommodement demandé, ainsi que le titre d'emploi et le numéro de demande du poste auquel vous postulez.