Career
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Internship Positions at General Motors for Spring 2025
2025 Summer Intern – Advanced Controls Systems for ADAS
Please see job description and role here.
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.
Internship Positions at Honda Research Institute USA for the Fall 2024
* Candidates must have the legal right to work in the U.S.A.
Computer Vision
- Road Scene Understanding through Computer Vision (Job Number: P23INT-40)
- Computer Vision in Low Light Scenes (Job Number: P23INT-43)
- Bird Eye View Perception (Job Number: P23INT-44)
Machine Learning/AI
- Behavior Modeling and Interactive Prediction (Job Number: P23INT-39)
- Learning Enhanced Motion Planning (Job Number: P23INT-41)
Robotics
- Visuotactile Perception for Robotic Manipulation (Job Number: P23INT-38)
- Trajectory Planning under Formal Methods Specification (Job Number: P23INT-42)
- Intention Aware Socially Conscious Motion Planning for Autonomous Navigation (Job Number: P23INT-45)
Interested applicants are encouraged to refer to the attached file for the description of each internship position and the required qualifications. A complete list of available positions including full-time positions can be found on our career’s website (https://usa.honda-ri.com/careers).
How to Apply: Submit applications through our website (https://usa.honda-ri.com/careers)
Internship Positions with AI Racing Tech for the 2024
Due Date: 6-15-2024
Contact: Dr. Allen Yang (yang@eecs.berkeley.edu)
2024 Planning System Intern –
The UC Berkeley AIracingTech team is looking to add a couple of students to its full- scale Autonomous Racing Team program. These positions are in the ART Planning subteam and offer an excellent opportunity for undergraduates, or recent grads, to get experience in current research and best practices in highly complex robotics / autonomous vehicle planning methods.
This is so much more that just moving a robot… This is strategically determining in real-time attack, defend, avoid, hold and retreat decision making for a 200mph racecar going head-to-head with other top university teams.
These are very hands-on positions, and you will be responsible for collaborative design and building specific capabilities and features that are integral to the operation and success of the ART autonomous racing stack. As a subteam Intern member you will be working with experienced ART team members.
Expect to learn a lot about how complex systems are continuously developed and improved. See how your work in design, code walk throughs and testing fit into the real world. Be knowledgeable or committed to learning the latest thinking is Planning theory, learning-based planning and Montecarlo based planning methods. The more C++, software engineering, and GIThub experience you have the better. The ability to be self-motivated and self-directed and yet be a fully committed team player will help you achieve overall success. Just like in the real world.
This is a potential multi-year opportunity and will materially add to your future industry or academic options. Must be available for minimum of 20 hours per week and available travel to US and international events.
2024 Controls System Intern –
The UC Berkeley AIracingTech team is looking to add a couple of students to its full- scale Autonomous Racing Team program. These positions are in the ART Controls subteam and offer an excellent opportunity for undergraduates or recent grads to get experience in current research and best practices in highly complex robotics / autonomous vehicle planning methods. We mix some of the latest MPC approaches with learning-based AI and balanced by the hard reality of the control methods that 1) must work… 2) must be reliable, and 3) has to provide the answer 50 times a second.
This is so much more that just moving a robot… This is strategically determining in real-time the optimum control signals to maximize the on-track performance of a 200mph, 2000# full scale racecar at the limits of the tires and real track conditions. No hiding in the SIM, super simplified physics, or with a 1/10 scale toy racecar. This is real… we race wheel-to-wheel going head-to-head with other top university teams. Can you help us teach our autonomous driver to beat a top human driver?
These are very hands-on positions, and you will be responsible for collaborative design and building specific capabilities and features that are integral to the operation and success of the ART autonomous racing stack. As a subteam Intern member you will be working with experienced ART team members.
Expect to learn a lot about how complex systems are continuously developed and improved. See how your work in design, code walk throughs and testing fit into the real world. Be well versed in math, physics and Control theory. The more C++, software engineering, and GIThub experience you have the better to take your ideas and put them in the stack. The ability to be self-motivated and self-directed, and yet be a fully committed team player will help you achieve overall success. Just like in the real world.
This is a potential multi-year opportunity and will materially add to your future industry or academic options. Must be available for minimum of 20 hours per week and available travel to US and international events.