Senior Software Engineer, ML Platform

Why Play Station?

Play Station isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The Play Station family of products and services including PlayStation5, PlayStation4, PlayStation

VR, Play Station Plus , acclaimed Play Station software titles from Play Station Studios, and more.

Play Station also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The Play Station brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.

Sr. Machine Learning Software Engineer - D2C - SPOC
Sony Interactive Entertainment (SIE) Play Station | San Diego, CA

Who We Are
At Sony Interactive Entertainment (SIE) Play Station, we create unforgettable gaming experiences—and we’re equally dedicated to building a world-class team. As a leader in interactive entertainment, Play Station operates at massive scale, supporting millions of players worldwide and processing billions of transactions annually across our digital ecosystem.

Our Store Publishing Operations & Commerce (SPOC) team is responsible for ensuring trust, security, and seamless transactions across Play Station’s digital store. We provide data-driven solutions to support platform services, customer experience, payments, fraud prevention, and risk management. Using advanced analytics and machine learning/AI, we help protect the commerce ecosystem, facilitate business growth, and optimize player experiences.

About the Role
This position is a hands-on engineering role with a broad range of responsibilities, from evolving and supporting machine learning/AI pipelines to building low-latency, high-throughput systems. You should be well-versed in running applications at internet scale on modern cloud architectures (e.g., AWS) using containerized and serverless workflows. If you’re passionate about large-scale machine learning projects, experimentation, automation, or real-time risk mitigation, we’d love to connect with you.

Key Responsibilities

Create Cloud Solutions:
Design and implement cloud solutions using AWS to ensure high performance, scalability, and reliability.

Core Infrastructure Development:
Develop and maintain core infrastructure for data streaming and processing, applying industry standards and innovative solutions.

ML/AI Pipeline Enhancement:
Build and enhance ML/AI pipelines supporting automation, experimentation, continuous integration/delivery, verification/validation, and model monitoring.

Automated Deployment:
Ensure all work is deployed in an automated, repeatable fashion, optimizing infrastructure for cost and efficiency.

Service Availability:
Guarantee high levels of service availability through being a part of an on-call rotation, following best practices for disaster recovery and business continuity.

Qualifications and Education Requirements

Educational Background:
Bachelor’s degree with 5+ years of related experience

Coding Proficiency:
Demonstrated experience with Java and Python

AWS Services

Competency:

Proficiency with common AWS services (EKS/ECS, Kinesis, Lambda, Dynamo

DB, SNS, SQS)

Systems Monitoring and Analytics:

Experience with systems monitoring, alerting, and analytics tools like Datadog, Splunk, New Relic, or AWS Cloud Trail

• Communication

Skills:

Strong communication skills to collaborate with multi-functional teams

Container Orchestration:

Experience with container orchestration and management (e.g., Kubernetes)

Data Science & Machine Learning:
Basic knowledge of Data Science, Machine Learning, and Large Language Models (LLMs)

Preferred Skills

AWS Certification

Stream Processing Expertise:

Experience with streams at internet scale (e.g., Kinesis, Kafka, Active

MQ)

• Linux Knowledge:
General knowledge of Linux

We sincerely appreciate the time and effort you’ve spent in contacting us, and we thank you for your interest in Play Station.

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