Location: London, UK 
 
The Gaming, Developer & Future Technology (GDFT) group are PlayStation's technology experts. We research and develop innovative technologies that push the boundaries of play, helping game developers make the best games on PlayStation.   

 As we continue to push the boundaries of technology, we are seeking a talented Machine Learning Engineer at the intersection of machine learning, computer vision, & video game development to join our dynamic R&D team.  

Our team is dedicated to advancing imitation learning to build intelligent agents capable of playing complex games. In this role, you will leverage foundation models and emerging techniques to drive research forward, deliver innovative solutions for customers, and contribute to publications that shape the future of gaming. 

 As a Machine Learning Engineer, you will be a key contributor to our research team, supporting the technical lead in driving technical excellence and innovation. You will be responsible for designing, implementing and optimising novel machine learning models and algorithms to perform challenging and diverse tasks. You will perform a central role in a highly collaborative and fast-moving environment where innovation and creativity are encouraged. 
 

What you’ll be doing: 

• Imitation Learning Development: Design, develop and deliver novel machine learning techniques to solve diverse tasks in game development, incorporating foundation models and high-level reasoning into the imitation process. 

• Research and Innovation: Contribute to the authorship of team research papers, presenting at relevant conferences. 

• Data Analysis: Perform data analysis and cleaning to uncover insights and patterns. 

• Collaboration and Creativity: Work with cross-functional teams to deploy machine learning models in production environments, solving issues and ensuring scalability and performance. 

• Communication: Present findings to stakeholders, communicating complex technical issues to both technical and non-technical colleagues. 

• Continuous Learning: Stay current with the latest machine learning and artificial intelligence research, attending top-tier conferences and communicating information across the team. 

• Prototyping: Quickly prototype new ideas and technologies to evaluate relevance and performance. 

• Inclusive Culture: Contribute to maintaining a culture of innovation, curiosity, creativity, and continuous learning within the team. 

What we are looking for: 

• Education: Master’s degree in computer science, electrical engineering, robotics, statistics, mathematics, or a related field. A PhD is preferred, but can be substituted with relevant work experience. 

• Domain Expertise:   

• 2+ years in machine learning (in industry or academia) with published research papers and proven expertise in Imitation Learning, Reinforcement Learning or Representation Learning. 

• Hands-on experience with foundation models at the intersection of language, vision, and action, such as multimodal Large Language Models (MLLMs), Vision-Language Models (VLMs), and Vision-Language-Action Models (VLAs). 

• Experience with Parameter-Efficient Fine-Tuning (PEFT) methods, including LoRA, for adapting large models efficiently. 

• Familiarity with transformer architectures, generative models and knowledge distillation techniques for real-time deployment in resource-constrained environments. 

• Proficiency in programming languages and frameworks relevant to machine learning, including Python, NumPy and Pytorch. 

• Strong understanding of data analysis, mining and preprocessing. 

• Experience with computer vision in areas such as Self-Supervised Learning (SSL), multimodal architectures, and post-training techniques is a plus. 

• Research Ambition: A passion for pushing the boundaries of artificial intelligence and a commitment to publishing in top-tier conferences and journals such IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar. 

• Interpersonal Skills: Excellent problem-solving, communication and interpersonal skills 

• Passion for Gaming: An interest in gaming and exploring the intersection of machine learning and game technology is desirable.