Machine Learning Engineer - Sports Technology

Job Description

EA SPORTS is one of the leading sports entertainment brands in the world, with top-selling videogame franchises, award-winning interactive technology, fan programs, and cross-platform digital experiences. Here, we create connected experiences that ignite the emotion of sport through industry-leading sports video games.
Our team in EA Vancouver is a passionate central group devoted to advancing the fields of character animation, physics, and AI in EA games: we work towards a future where these essential components all play together to create realistic and compelling characters and exciting experiences. Our technology is shared across multiple games in EA, including Madden NFL, EA Sports FC, NHL® Hockey, EA SPORTS UFC, Battlefield, and many others.

We are seeking research engineers with a practical mindset, passionate about creating useful tools and innovative features, eager to see their work impact fellow developers and millions of gamers. Reporting to the Principal Software Engineer, the Machine Learning engineer will join us in pushing the boundaries of game fidelity and bringing our characters to life!

Your Responsibilities:
• Stay up to date with research in the field of Machine Learning.
• Propose and develop novel Machine Learning-based solutions to solve problems in character animation, agent behavior, physics, and content generation.
• Design and implement Machine Learning solutions that consider game development requirements:
• Provide easy-to-use workflows to assist users by minimizing repetitive human intervention and empower user creativity.
• Empower users with creative control over model behavior and streamline the process of iteration and debugging.
• Optimize models and code to minimise training and inference time.
• Collaborate with content creators and other software engineers to ensure that our tools are maintainable, effective, and easy to use.

Your Qualifications:
• Bachelor's degree in computer science, applied math, statistics, machine learning or equivalent.
• Expert-level proficiency in Python software development:
• Advanced features like generators, decorators, and context managers.
• Experience writing efficient, maintainable, and scalable Python code.
• Knowledge of linear algebra, statistics, and mathematical optimization techniques.
• Knowledge of Machine Learning:
• At least 1-2 years of experience in the field with a demonstrated practical approach to problem solving.
• PyTorch expertise, optional experience with TensorFlow, JAX, and other machine learning frameworks.
• Focus on Deep Learning and Deep Reinforcement Learning approaches, applied to character animation and agent-behavior.
• Proficient in data manipulation, analysis and visualization using tools like NumPy, pandas/polars, three.js, d3.js and matplotlib.
• Master's degree in computer science, applied math, statistics, machine learning or equivalent.

GRADE 21

BC COMPENSATION AND BENEFITS

The base salary ranges listed below are for the defined geographic market pay zones in these locations. 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 base salary 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, education, 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 $93,700 - $153,900 CAN Annually

Base salary is just one part of the overall compensation at EA. We also offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.

Jobcode: Reference SBJ-r0q9be-3-14-134-62-42 in your application.