Machine Learning Co-op (PhD Student)

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.EA SPORTS is one of the most iconic brands in entertainment – connecting hundreds of millions around the world to the sports they love through a portfolio of industry-leading video games.

The EA SPORTS Catalyst Research and Innovation Team is dedicated to pioneering research that propels the gaming industry forward. We aim to redefine the gaming experience by integrating innovative technologies and exploring new paradigms in game development. We focus on forward-looking experimentation and harness cutting-edge technology to uncover what makes games fun for humans.

We are seeking a PhD candidate with strong Machine Learning skills and research experience in world models and/or generative AI. Our aim is to discover new technologies and interactive experiences that will redefine gameplay. This paid position reports to the Head of Research & Innovation. You will start September 2, 2025 for the duration of a 4 or 8-month term. You will be working in a hybrid work environment for 3 days per week from our EAV Studio in Burnaby.

Your Responsibilities

• Conduct research on generative world models and their applications in video games.

• Collaborate with researchers and game developers to brainstorm, discuss, and implement innovative solutions.

• Design and implement cutting-edge machine learning algorithms by analyzing and refining ML techniques to enhance model performance.

• Develop a proof of concept to demonstrate interactive experiences using world models.

• Work with cross-functional teams to communicate research plans and progress.

• Write reports and present research findings internally.

• Explore opportunities to share your work through publications and open-source contributions.

Your Qualifications

• You must be available for the entire duration of the work term with us.

• You must return to school for at least one semester following your co-op experience with us.

• Currently pursuing a Ph.D. in Computer Science, Machine Learning, Artificial Intelligence or a related field.

• Experience with programming languages like Python or C++.

• Proficient in machine learning frameworks such as PyTorch or TensorFlow.

• Skills in training machine learning models, including data collection, implementation, and evaluation.

• Publications, presentations or related contributions in world models or generative AI.

We are only considering students who will be enrolled in an accredited degree program throughout this co-op, and returning to school for at least one semester following your work term at EA. You must be legally authorised to work in Canada on a full-time basis during the co-op term. Visa sponsorship and relocation are not available for this position.

BC COMPENSATION AND BENEFITS

The base salary ranges listed below are for the defined geographic market pay zones in these states. If you reside outside of these locations, a recruiter will advise on the base salary range and benefits for your specific location.

EA has listed the pay ranges it in good faith expects to pay applicants for this role in the locations listed, as of the time of this posting. Salary offered will be determined based on numerous  relevant business and candidate factors including, for example, degree type (e.g. Bachelor’s, Master’s, PhD), what stage you are in your degree journey (i.e. freshman, sophomore, etc.), qualifications, certifications, experience, skills, geographic location, and business or organizational needs.

BASE SALARY RANGES

    • British Columbia (depending on location e.g. Vancouver vs. Victoria):

      º 65,000 - $70,000 CAN Salary

The pay is just one part of the overall compensation at EA.  We also offer a package of benefits including 80 hours per year of sick time (prorated based on scheduled hours per week if less than full-time), 16 paid company holidays per year, medical insurance, and 401(k).