MLOps Engineer

Description

The company makes social casino mobile games, and this role sits in its machine learning area.

The MLOps team is hiring an engineer to build and run the platform that moves ML and AI systems into production.

Your work covers real-time model serving, the CI/CD and infrastructure behind it, and the tools that help ML Engineers and Data Scientists ship, track and monitor models.

The work directly affects the company's products and what players experience.

The company has over 7,300 employees worldwide across three business units.

Responsibilities

• Serve models as reliable, low-latency, high-throughput real-time APIs, with attention to caching and scaling.
• Design and run the serving and deployment infrastructure, including containers, Kubernetes, and serving frameworks such as KServe, Triton or BentoML where they fit.
• Build and maintain CI/CD pipelines for models, and orchestrate training and retraining workflows, for example in Airflow.
• Own the platform side of experiment tracking and the model registry, covering versioning, lineage, promotion and governance so releases are controlled and reproducible.
• Build monitoring and observability for model and system health, including metrics, logs, traces and alerts, for ML Engineers to use.
• Make pipelines and environments reproducible, and harden systems with retries, timeouts, graceful degradation and rollback.
• Work with ML Engineers and Data Scientists to move prototypes into production, and with engineering on deeper system design.

Requirements

• 4+ years in ML infrastructure, ML platform or MLOps roles, ideally within a dedicated MLOps or platform team.
• Strong software and systems engineering foundations, with an engineering or Computer Science background.
• Proven experience serving real-time, low-latency models, with a solid understanding of caching, concurrency and p95/p99 performance.
• Hands-on experience with Docker, Kubernetes, CI/CD and a cloud platform such as GCP, AWS or Azure.
• Experience with workflow orchestration (Airflow, Prefect, Kubeflow or similar) and with experiment tracking or model registry tools (MLflow, Weights & Biases).
• Solid Python skills and experience running production services and their observability stack, such as Prometheus and Grafana.
• Experience with Snowflake or a similar cloud data warehouse.
• Experience supporting GenAI or LLM applications in production, including serving, evaluation infrastructure and vector databases.
• Exposure to designing AIOps-oriented infrastructure.
• Interest in the modeling side, enough to collaborate closely with ML Engineers. You do not need to be a researcher.

Conditions

This is a hybrid role with 3 days a week in the office.

Travel is minimal, up to 5%.

Depending on the role, you may need to register with the Nevada Gaming Control Board (NGCB) or other gaming jurisdictions where the company operates.

Pay is set by your skills, experience, qualifications and location, and the company rewards individual impact through pay for performance.

Specific pay and benefit details for this role will be shared during recruitment.

Content was reviewed and enhanced with AI-assisted tools, and final role requirements and hiring decisions remain subject to human review and approval by the company.

Benefits

• Depending on role and location, you may be eligible for annual bonuses and incentives.
• Health and wellbeing benefits, paid time off, retirement plans and insurance cover may be available, along with other local or statutory benefits.