Senior ML Platform Engineer — Self-Service & Deployment

SCIENTIFIC GAMES; Toronto; Hybrid; CAD 110,000 - 190,000; Full time

Job summary

Scientific Games is seeking a Senior Machine Learning Engineer to help build the foundations of our ML platform from the ground up. This role emphasizes self-service tooling and golden paths that enable Data Scientists to move models from experimentation to production across batch and real-time use cases.

You will collaborate with Staff MLEs, Data Scientists, and platform stakeholders to establish reusable infrastructure, deployment workflows, observability standards, and developer experience

Qualifications

• 3+ years of hands on experience in ML engineering, platform engineering, or production ML systems.
• Proven experience building production batch and real-time ML systems.
• Experience working closely with Data Scientists to productionize models and experimentation workflows.
• Strong experience building reusable tooling, frameworks, or internal developer platforms.

Responsibilities

• Build reusable self-service tooling for model packaging, deployment, batch inference, and real-time serving.
• Develop platform capabilities that enable Data Scientists to independently deploy, monitor, and iterate on their own models in production.
• Design CI/CD pipelines for automated training, validation, shadow deployment, canary rollout, rollback, and full production promotion workflows.
• Establish golden-path templates, SDKs, CLIs, and reference implementations to standardize ML system delivery.
• Contribute to observability standards across model health, latency, feature freshness, data quality, and business KPI monitoring.
• Partner with Staff MLEs to shape the first-generation architecture of the ML platform.

Skills

Python programming

Software engineering fundamentals

Collaboration with Data Scientists

Developer experience

A/B testing tooling

Education

Master’s degree in Computer Science, Engineering, Machine Learning, Software Engineering, or related STEM field

Bachelor’s degree in related STEM field with strong equivalent industry depth

Tools

PyTorch

TensorFlow

Docker

Kubernetes

GitHub Actions

MLflow

Model registry

Databricks

PySpark

Airflow

Job description

Scientific Games is seeking a Senior Machine Learning Engineer to help build the foundations of our ML platform from the ground up. This role emphasizes self-service tooling and golden paths that enable Data Scientists to move models from experimentation to production across batch and real-time use cases.

You will collaborate with Staff MLEs, Data Scientists, and platform stakeholders to establish reusable infrastructure, deployment workflows, observability standards, and developer experience