Software Development Engineer in Test, ML

PlayStation Global•San Mateo, CA

16h•Hybrid

About The Position

Sony Interactive Entertainment (SIE) is seeking a Quality Engineer to join their Machine Learning Platform engineering team. This role is crucial for delivering impactful insights and building dynamic, interactive experiences for millions of PlayStation users. The AI/ML Engineering Group focuses on optimizing interactions across PlayStation experiences and systems by designing, coding, training, documenting, deploying, and evaluating large-scale machine learning systems. The Quality Engineer will work in an agile environment, collaborating with teams across Engineering, Security, Architecture, and Product, and will be immersed in AI/ML technologies, tools, and processes to advance technical objectives and architectural initiatives.

Requirements

3 - 5 years of experience in software quality engineering, test automation, or SDET roles
Bachelor's degree or equivalent
Proficiency in one or more of the following programming languages: Python, Java, Scala, or Go
Hands-on experience building and maintaining automated test frameworks (e.g., pytest, JUnit, TestNG, etc.)
Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker, etc.)
Familiarity with CI/CD tools (Jenkins, GitHub Actions, ArgoCD, etc.) and integrating automated testing into delivery pipelines
Experience with API and service-level testing for distributed systems
Strong verbal and written communication skills
Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, etc.) for validating service health

Nice To Haves

Experience testing online services with high RPS and low latency requirements
Exposure to ML platforms, model serving infrastructure, or inference systems (Seldon, KServe, Ray Serve, etc.)
Experience with performance and load testing tools (Locust, k6, Gatling, JMeter, etc.)
Experience with Databricks or similar ML platform tooling

Responsibilities

Develop, maintain, and execute test plans, test cases, and test automation for the in-house developed Inference Service and related ML platform components.
Design and implement integration, regression, and performance test strategies to validate new releases of the Online Inference service.
Build and maintain automated testing frameworks and CI/CD test pipelines to ensure quality assurances are met before production deployments.
Collaborate with ML engineering and platform teams to define acceptance criteria and validate the productionization of ML models through the inference pipeline.
Create and maintain performance and load testing suites to verify inference service scalability, latency requirements, and reliability under production-like conditions.
Develop and track quality metrics, defect trends, and test coverage reports to provide visibility into release readiness.
Participate in design and architecture reviews to identify testability concerns and quality risks early in the development lifecycle.
Contribute to improving team testing practices, tooling, and processes in support of MLOps best practices.