Machine Learning Intern - PhD

Role Summary:

Join the Game Service ML team within PlayStation Global Research & Development (R&D) at Sony Interactive Entertainment (SIE) and gain hands-on experience researching multimodal AI and anomalous behavior detection for video games.

As a Machine Learning Research Intern, you'll explore how gameplay video, audio, and/or controller inputs can be used to understand gameplay behaviors, identify unusual patterns, and automatically detect bugs and glitches during game development, certification and compatibility testing. Your research will help explore ways to make game QA more efficient and improve gaming experiences for millions of players.

Based in San Mateo, you'll collaborate with the London-based Anomaly Detection focus team and receive joint supervision from the San Mateo-based GameLens focus team. You'll work alongside experienced researchers and engineers across PlayStation Global R&D, with opportunities to investigate new research approaches, develop practical solutions, and contribute to findings that may be suitable for publication at a research conference.

What You’ll Be Doing:

• Research and develop vision-language and multimodal models for game scene understanding and anomaly detection, exploring topics such as self-supervised learning, contrastive learning, state-space models, multimodal AI, vision-language models, representation learning, and anomaly detection.

• Design and conduct experiments to evaluate model performance, behaviour and generalisation, including exploring new methods and evaluation metrics.

• Develop working prototypes that apply research ideas to real-world game QA challenges, including identifying unexpected gameplay behaviors, bugs, and glitches.

• Analyze experimental results, identify opportunities for improvement, and explore how machine learning research can support game development, certification and compatibility testing.

• Collaborate with researchers and engineers to share findings, discuss technical challenges, and help shape future research directions.

• Explore opportunities to develop research findings into a paper for submission to a suitable research conference.

• Gain practical experience managing an ML research project from initial research questions through experimentation, evaluation, and potential real-world application, with mentorship from experienced researchers and engineers.

What We’re Looking For:

• Currently pursuing a PhD in Computer Science, Machine Learning, Computer Vision, Natural Language Processing or a related field, ideally in the later stages of your program.

• Strong research background in machine learning, computer vision, multimodal learning or related areas, with experience independently exploring open-ended research problems.

• Proficiency in Python programming and hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.

• Experience designing experiments, evaluating machine learning models, and interpreting research results.

• Strong problem-solving, communication, and collaboration skills, including the ability to seek, receive and incorporate feedback from researchers and engineers.

• Publication record in relevant conferences (e.g. NeurIPS, ICML, ICLR, CVPR, ACL or EMNLP).

• Interest in gaming, game engines, or the intersection of machine learning and game technology is highly desirable.

Eligibility

• Students with expected graduation between May 2026 and December 2029 from an accredited university. Advanced Degree - PhD

• Able to work during one of the following periods: May 17th - August 6th or June 14th - September 3rd. Relocation assistance is available for eligible candidates.

• Must be available for the entire 12-week internship period.
  

At this time, SIE will only consider applicants who are authorized to work for any employer in the United States and who will not require work visa sponsorship from SIE now or in the future to maintain their authorization to work in the United States.

Our intern positions offer a fixed hourly pay rate. Please note that the pay rate is exclusive to the internship period and may not reflect what pay may look like following the completion of an internship.