Senior ML Platform Engineer

Scientific Games; Toronto; Hybrid; CAD 120,000 - 180,000; Full time

Job summary

Scientific Games is seeking a Senior Machine Learning Engineer to help build the foundations of our self-service ML platform from the ground up. You will work with Staff MLEs, Data Scientists, and platform teams to enable models to move from experimentation to reliable production deployment across batch and real-time use cases.

This role will start remotely and transition to a hybrid role. Candidates must be local to Toronto, ON, to collaborate closely with teams and align with our physical

Qualifications

• Master’s degree in Computer Science, Engineering, Machine Learning, Software Engineering, or related STEM field
• 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 and collaborating with Data Scientists

Responsibilities

• Build reusable self-service tooling for model packaging, deployment, batch inference, and real-time serving
• Develop platform capabilities enabling Data Scientists to independently deploy, monitor, and iterate on models in production; create ML workflows and inference APIs
• 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, data quality, and business KPI monitoring
• Partner with Staff MLEs to shape the first-generation architecture of the ML platform

Skills

Python

Software engineering

PyTorch

TensorFlow

Kubernetes

API design

Education

Master’s degree in Computer Science or related STEM field

Bachelor’s degree with strong equivalent industry depth

Tools

Docker

Kubernetes

MLflow

Databricks

Job description

Scientific Games is seeking a Senior Machine Learning Engineer to help build the foundations of our self-service ML platform from the ground up. You will work with Staff MLEs, Data Scientists, and platform teams to enable models to move from experimentation to reliable production deployment across batch and real-time use cases.

This role will start remotely and transition to a hybrid role. Candidates must be local to Toronto, ON, to collaborate closely with teams and align with our physical