Senior ML​/AI Software Engineer

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 Play Station®5, Play Station®4, Play Station®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.

At Sony Interactive Entertainment (SIE) Play Station, we create unforgettable gaming experiences—and we're just as committed to building a world-class team. As a leader in interactive entertainment, Play Station operates at a 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. By using advanced analytics and machine learning/AI, we assist in protecting the commerce ecosystem, facilitating business growth, and optimizing player experiences.

We are seeking a Senior ML/AI Engineer to lead the design, optimization, and deployment of large-scale automation efforts, utilizing LLMs and generative AI as appropriate. This role sits at the intersection of machine learning, backend engineering, and cloud-scale infrastructure, focusing on building intelligent systems that power our teams.

The ideal candidate has hands‑on experience building scalable, automated systems. You combine backend engineering expertise with applied AI knowledge, using technologies like Lang Chain, vector databases, and LLM APIs alongside microservices, Kubernetes, Terraform, and CI/CD pipelines to create resilient, intelligent systems. You’ll partner closely with devOps, data science, and data engineering to deploy scalable, reliable, and cost‑efficient automation solutions that increase efficiencies and accelerate innovation across the organization.

Automate Workflows: Architect, build, test, and monitor AWS‑based workflows to solve critical business problems.

Microservices and APIs: Develop microservices for ML‑driven applications using Python or Java, ensuring scalability and resilience.

Service Availability: Guarantee high levels of service availability through participation in an on‑call rotation, following best practices for disaster recovery and business continuity.

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

Educational Background: Bachelor’s degree with 6+ years of experience in machine learning, backend engineering, or AI platform development.

Coding Proficiency: Demonstrated experience with Java and Python.

Cloud

Competency:

Proficiency with common AWS services or equivalent such as EKS/ECS, Kinesis, Lambda, Dynamo

DB, SNS, and SQS.

Systems Monitoring and Analytics: Knowledge of systems monitoring, alerting, and analytics using tools such as Datadog, Splunk, New Relic, or AWS Cloud Trail.

Communication

Skills:

Demonstrated success in cross‑functional collaboration.

LLM Expertise: Proven experience developing, evaluating and orchestrating agentic workflows.

MLOps and Distributed Systems: Hands‑on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD.

Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow.

Multi‑Modal LLM Systems: Experience with multi‑modal LLM systems (text + image embeddings).

AI Observability and…