Description
GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.
Work Arrangement :
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Mountain View Technical Center three times per week, at minimum.
The Team:
The Advanced Driver Assistance Systems (ADAS) team is at the forefront of developing cutting-edge technologies that enhance vehicle safety, performance, and autonomy. We specialize in designing, testing, and deploying intelligent systems that provide critical assistance to drivers, such as adaptive cruise control, lane-keeping assistance, automated braking, and collision avoidance. Our team works on a wide range of systems, integrating data from sensors like lidar, radar, and cameras to create robust, real-time solutions for autonomous navigation and decision-making.
As part of the ADAS team, you will collaborate with experts in machine learning, control systems, sensor fusion, and data science to develop advanced algorithms for vehicle autonomy. We focus on using both model-based and data-driven approaches to optimize the performance of ADAS functionalities, ensuring safety, reliability, and scalability across diverse driving environments. We emphasize real-time control solutions, hardware-in-the-loop (HIL) testing, and simulation to evaluate and refine the effectiveness of our systems.
Our multidisciplinary team fosters a collaborative environment where cutting-edge research is applied to real-world challenges in the automotive sector. We leverage the latest advancements in machine learning, data science, and control theory to push the boundaries of what’s possible in autonomous vehicle technologies. By joining our team, you will play a pivotal role in shaping the future of mobility, driving innovation in the transition towards fully autonomous vehicles
What You’ll Do:
We are seeking a PhD Advanced Controls Intern with a strong focus on machine learning (ML) and automation to join our innovative research and development team. In this role, you will leverage advanced control theory, reinforcement learning, and predictive modeling to develop intelligent automation solutions for complex systems. You will collaborate with multidisciplinary teams to design, simulate, and implement control strategies that optimize performance, enhance efficiency, and adapt to dynamic environments. The ideal candidate is pursuing a PhD in Control Systems, Robotics, Machine Learning, or a related field and is passionate about applying their expertise to solve real-world challenges in automation and intelligent systems.
Key Responsibilities:
-
Develop advanced control algorithms leveraging machine learning and reinforcement learning to optimize the performance of autonomous vehicle systems and Advanced Driver Assistance Systems (ADAS)
-
Design, simulate, and validate control strategies for path planning, trajectory optimization, and decision-making in dynamic traffic environments
-
Analyze sensor data, including lidar, radar, and cameras, to enhance vehicle perception and integrate it into intelligent control systems
-
Collaborate with cross-functional teams to implement real-time control solutions for autonomous navigation and adaptive vehicle behavior
-
Conduct system-level simulations to evaluate the robustness and scalability of control strategies under varying operational conditions
-
Research and apply predictive modeling techniques to anticipate and mitigate potential safety risks in autonomous and ADAS functionalities
-
Support hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing to ensure seamless integration of advanced controls into vehicle systems
-
Stay updated on the latest advancements in control theory, machine learning, and autonomous vehicle technologies, incorporating innovative approaches into ongoing projects
-
Document methodologies, experimental results, and key insights to support knowledge sharing and collaboration within the team
[Additional Description]
Required Qualifications:
-
Currently pursuing a PhD in Control Systems, Robotics, Machine Learning, Electrical Engineering, Computer Science, Data Science, or a related field
-
Must be graduating after December 2025
-
Able to work fulltime, 40 hours per week during the summer months
What will give you a Competitive Edge (Preferred Qualifications):
-
Strong foundation in control theory, machine learning, optimization, and data science methodologies
-
Experience developing and implementing algorithms for autonomous systems, including path planning, trajectory optimization, and dynamic decision-making
-
Proficiency in programming languages such as Python, C++, or MATLAB, and familiarity with libraries and frameworks for data science and machine learning (e.g., TensorFlow, PyTorch, Scikit-learn).
-
Knowledge of sensor fusion techniques and data processing for lidar, radar, and cameras, and experience analyzing large, complex datasets
-
Hands-on experience with simulation environments for autonomous vehicles (e.g., CARLA, Gazebo) and data science tools (e.g., pandas, NumPy, Jupyter Notebooks)
-
Ability to design and validate control strategies using both model-based and data-driven approaches, including reinforcement learning and predictive analytics
-
Familiarity with hardware-in-the-loop (HIL), software-in-the-loop (SIL), and real-world testing methodologies for autonomous systems
-
Strong analytical and problem-solving skills, with demonstrated experience in using statistical and machine learning techniques to extract insights from data
-
Excellent written and verbal communication skills for documenting results, creating visualizations, and presenting findings to both technical and non-technical audiences
Start dates for this internship role are May & June of 2025.
Compensation:
-
The monthly salary range for this role is $9,400-$11,100, dependent upon class status and degree
-
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2025 Student Program
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
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 Careers.Accommodations@GM.com 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.