At Sony Interactive Entertainment (SIE) PlayStation, we create unforgettable gaming experiences—and we're just as committed to building a world-class team. As a leader in interactive entertainment, PlayStation 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 PlayStation’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. **About the Role:** 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 LangChain, 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 accelerates innovation across the organization. **Key Responsibilities:** - 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. **Qualifications and Education Requirements:** - 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, DynamoDB, SNS, and SQS. - Systems Monitoring and Analytics: Knowledge of systems monitoring, alerting, and analytics using tools such as Datadog, Splunk, New Relic, or AWS CloudTrail. - 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. **Preferred Skills:** - 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 Evaluation: Exposure to AI observability, prompt evaluation frameworks, and safety alignment tools. - Vector Database Knowledge: Understanding of vector databases and retrieval workflows. **Benefits:** - Not explicitly listed in the posting, but implied benefits include being part of a leading global entertainment company, inclusive environment, and opportunities for innovation and growth. **Salary Range:** - Not explicitly listed in the posting or JSON data. No salary information available.