Hybrid MLOps Engineer: Train, Deploy & Observe AI Models

Electronic Arts Ltd; Redwood (TX); Hybrid; USD 154,000 - 256,000; Full time

Benefits offered by this job

Paid time off

Medical/dental/vision insurance

401(k)

Job summary

Electronic Arts (EA) is seeking an experienced MLOps Engineer to optimize model training and deployment. You will partner with researchers, and the Lead Infrastructure Engineer to translate requirements into durable operational processes for scalable ML pipelines.

Hybrid role onsite three days a week in Redwood City, Montreal, or Vancouver, with responsibilities spanning data-path engineering, observability, and GPU utilization metrics. Strong Python and PyTorch expertise required.

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

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.

Skills

Python

MLOps

Model optimization

Distributed ML

Observability

AWS (EC2/S3/EKS)

Containerization/CI/CD

PyTorch

Data processing (Ray/Spark)

GPU utilization

Tools

Ray

Spark

Parquet

Arrow

Lance

Prometheus

Grafana

EC2/GPU

S3

EKS

Docker

CI/CD for ML

Job description

Electronic Arts (EA) is seeking an experienced MLOps Engineer to optimize model training and deployment. You will partner with researchers, and the Lead Infrastructure Engineer to translate requirements into durable operational processes for scalable ML pipelines.

Hybrid role onsite three days a week in Redwood City, Montreal, or Vancouver, with responsibilities spanning data-path engineering, observability, and GPU utilization metrics. Strong Python and PyTorch expertise required.