Description & Requirements

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.

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.

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At EA, we believe games are powerful because they bring together multiple ways people engage: play, watch, create, and connect. And increasingly, the biggest entertainment platforms aren't just places to consume content — they're places where communities build.

Creator-made content is already a proven part of EA's history — from community creation tools in Battlefield to The Gallery in The Sims 4. We believe new creative technologies and tools will expand how players engage with and contribute to our experiences, supported by thoughtful product design, safety systems, and global reach. Our focus is on enabling more players to participate in creative expression by making creation easier, safer, and more rewarding.

As an MLOps Engineer, you will work closely with researchers to optimize models, help shape the data they need for training, and instrument the system to measure and improve model performance.



Working in close partnership with the Lead Infrastructure Engineer and Research Leads, you will translate requirements into durable operational processes and ensure the fleet operates effectively.

You will report to the Head of Data & Infrastructure.

Responsibilities

- You will optimize how our models train and serve.
- You will build the streaming data path from lake to GPU.
- You will make our data formats a deliberate choice.
- You will instrument all of it including Per-job GPU utilization, queue depth and job success rate, cost per experiment, data-loader stall time, and serving latency percentiles.
- You will land the training and experiment telemetry into one place researchers and planners trust.

Qualifications

- 8+ years of engineering experience
- 4+ years building and operating ML systems in production
- Expertise in Python
- Comfort reading and modifying framework-level code — PyTorch, and an inference server such as vLLM, SGLang or TensorRT-LLM
- Demonstrated model or inference optimization work
- Hands‑on experience with distributed data processing for ML (including Ray, Spark, or equivalent) and columnar and ML‑native formats (such as Parquet, Arrow, Lance, or similar)
- Practical observability skills including Prometheus, Grafana, or equivalent




- Working knowledge of AWS compute and storage as they apply to ML workloads — EC2 GPU instances, S3 and its performance tiers, EKS
- Experience with containerization and CI/CD for ML artifacts and a reproducibility instinct

This is a hybrid role, onsite three days a week, in Redwood City, Montreal, or Vancouver.

We want to connect you with job opportunities that align with your interests, skills, and expertise. When you create an EA Careers Account and are logged into the portal, you can click “Get Recommendations” to view a curated list of job openings. These recommendations are enhanced by automated processing, including artificial intelligence, and take into account your skills and experience. However, all employment decisions are made by our hiring teams, not by automated systems.

Pay Transparency - North America

Compensation And Benefits

The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).

PAY RANGES

- British Columbia (depending on location e.g. Vancouver vs. Victoria) *$141,400 - $204,400 CAD
- California (depending on location e.g. Los Angeles vs. San Francisco) *$165,000 - $256,000 USD

Pay is just one part of the overall compensation at EA.

In the US, we offer a package of advantages including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year

📌 Développeur.se - opérations liées à l’apprentissage automatique / MLOps Engineer (Montreal)
🏢 Electronic Arts (EA)
📍 Montreal