Software Engineer, ML Solutions - Game Production Solutions (GPS)

Who we are

Game Production Solutions is a new division in Creative Technologies at Electronic Arts. In the Game Production Solutions group we build solutions for our customers (Game Teams / Creators). We empower game creators to make an outsized impact with our technology.

Your work with us

We are working on projects related to generative AI and Machine Learning, focused on Generative AI for game assets. The platform we are building is to power Generative AI for game creators across EA. We are using powerful models fine-tuned and adapted for asset creation, where performance, ease of use, and security are priorities.

As an engineer in this group, you will deploy AI/ML solutions for our game creators: taking the solution from dev to production, ensuring security compliance, implementing scaling technology, and so on will all be a part of your role.

In addition to the focus on MLOps, this role also demands adeptness in traditional DevOps and infrastructure responsibilities. You will take a hands-on approach to managing the workflows for asset pipelines, partnering with Software Engineers who author pipeline code, and doing hands-on, daily management of cloud infrastructure.

You will report into the Technical Director that oversees DevOps and MLOps in our group.

This position is for you if …

• You're keen on forging a career path in DevOps, MLOps, and cloud infrastructure.
• You enjoy being a hands-on contributor, in both architecture / design and implementation.
• You're willing to step beyond your comfort zone and face new challenges.
• You enjoy working in a versatile team of Software Engineers and Technical Artists.

Important Responsibilities

• Manage large-scale data sets: Create solutions for the collection, storage, cleaning, and labelling of training data (game assets.)

• Build end-to-end machine learning systems: Including data collection/labelling, training pipelines, model deployment, and monitoring

• Automation: Automate the CI / CD process for model training.

• Deployment: Deploy services and models to cloud infrastructure at scale.

• Monitoring: Monitor ongoing execution and performance.

• Documentation: Create documentation on the processes and technologies.

• Collaboration: You will collaborate with partners around the company to ensure compliance with infrastructure, security, and development standards.

Qualifications

• 5+ years of experience as an engineer focused on DevOps, MLOps, or a similar domain.
• Proficiency in software engineering best practices: version control, testing, code review.
• Proficient in using Python, Spark SQL to query large datasets.
• Expertise in ML frameworks like PyTorch, TensorFlow.
• Experience working with cloud services at scale (one of AWS, Azure, or Google) using IAC tools such as Terraform.
• Experience integrating / working with MLOps pipelines and products like Databricks or similar.
• Comfortable working in a remote or hybrid environment.
• Willing to travel to meet with team members and partners in person.
• Bachelor's degree in one of Computer Science (or related technical field) or equivalent practical experience.

Ceci ne s’applique pas au Québec. 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 $115,100 - $161,200 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.