Research Intern (PhD), Autonomy

About Stack:

Stack is developing revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency of modern operations. Stack's autonomous technology incorporates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies, empowering us to create innovative solutions that address the needs and challenges of the dynamic trucking transportation industry. With decades of experience creating and deploying real world systems for demanding environments, the Stack team is dedicated to developing an autonomous solution ecosystem tailored to the trucking industry's unique demands.

If you are an Internal Candidate, please apply via our Internal Job Board.

Intern Program:

We are seeking the best and brightest interns that are eager to contribute to transformative AI solutions. As an early-stage start up, we expect our interns to be an integral part of the team while gaining collaboration opportunities with industry leaders to grow your career and research.

We welcome students who are enrolled in university, pursuing a doctorate degree and are currently located in the United States. Our 2027 Summer internship will be at least 12 weeks in duration (note: we may have flexibility to continue into the fall semester). We offer competitive pay and support CPT. Please note we are a remote first company- interns already based in the Pittsburgh area are welcome to work in-person.

About The Team:

Our Autonomy team brings together experts in artificial intelligence, perception, machine learning, decision-making, and controls to drive the most visible and high-impact initiatives behind our autonomous vehicle product. As an intern, you’ll dive into cutting-edge research challenges and contribute to breakthroughs that directly shape the future of our technology.

Potential internship research areas could be...

• Autolabeling
• 3D perception/tracking/SLAM
• Long range perception
• Automatic mapping
• Prediction
• Deep decision making
• World Models
• Distributed, multi-stage ML architectures

Minimum Qualifications:

• Currently enrolled in a PhD program in a relevant field (3+ years into program preferred)
• Strong programming skills in Python or C++
• Experience with ML frameworks such as PyTorch
• Strong foundation in Computer Vision, Machine Learning, Simulation, Reinforcement Learning
• Ability to develop, train, and validate AI/CV/ML models
• Experience in SOTA deep learning techniques, e.g. multi-modal foundational models
• Experience working and communicating cross functionally in a team environment

Preferred Qualifications:

• Track record of research excellence demonstrated by grants, fellowships, patents, or publications at top conferences such as CVPR, ICCV, ICRA, IROS, etc.
• Strong track-record of published research
• Strong programming experience using python and pytorch
• Prior software engineering or research experience in an internship, work experience, or widely used contributions in open source repositories (e.g. GitHub)

We are proud to be an equal opportunity workplace. We believe that diverse teams produce the best ideas and outcomes. We are committed to building a culture of inclusion, entrepreneurship, and innovation across gender, race, age, sexual orientation, religion, disability, and identity.

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Please Note: Pursuant to its business activities and use of technology, Stack AV complies with all applicable U.S. national security laws, regulations, and administrative requirements, which can restrict Stack AV’s ability to employ certain persons in certain positions pursuant to a range of national security-related requirements. As such, this position may be contingent upon Stack AV verifying a candidate’s residence, U.S. person status, and/or citizenship status. This position may also involve working with software and technologies subject to U.S. export control regulations. Under these regulations, it may be necessary for Stack AV to obtain a U.S. government export license prior to releasing its technologies to certain persons. If Stack AV determines that a candidate’s residence, U.S. person status, and/or citizenship status will require a license, prohibit the candidate from working in this position, or otherwise be subject to national security-related restrictions, Stack AV expressly reserves the right to either consider the candidate for a different position that is not subject to such restrictions, on whatever terms and conditions Stack AV shall establish in its sole discretion, or, in the alternative, decline to move forward with the candidate’s application.