About the CompanyScientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries. From cutting‐edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we elevate play every day. We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation, legendary performance, and unwavering security to responsibly propel the global lottery industry ever forward.Position SummaryAbout the RoleWe are looking for a Senior Machine Learning Engineer to help build the foundations of our machine learning platform from the ground up. This role is not about creating a centralized gatekeeping team. Instead, the mission is to build self‐service ML tooling and golden paths that enable Data Scientists to independently take models from experimentation to reliable production deployment across batch and real‐time use cases. You will partner closely with Staff MLEs, Data Scientists, and platform stakeholders to establish the first generation of reusable ML infrastructure, deployment workflows, observability standards, and developer experience patterns that scale across the organizationLocationThis role is based out of Toronto.Key ResponsibilitiesBuild reusable self‐service tooling for model packaging, deployment, batch inference, and real‐time servingDevelop platform capabilities that enable Data Scientists to independently deploy, monitor,



and iterate on their own models in productionBuild foundational ML workflows including model registry, environment promotion, rollback, feature access patterns, and inference APIsDesign CI/CD pipelines for automated training, validation, shadow deployment, canary rollout, rollback, and full production promotion workflowsEstablish golden‐path templates, SDKs, CLIs, and reference implementations to standardize ML system deliveryContribute to observability standards across model health, latency, feature freshness, data quality, and business KPI monitoringPartner with Staff MLEs to shape the first‐generation architecture of the ML platformRequired QualificationsEducationMaster's degree in Computer Science, Engineering, Machine Learning, Software Engineering, or another related STEM fieldBachelor's degree in a related STEM field with robust equivalent industry depth is also acceptableExperience3+ years of hands‐on experience in ML engineering, platform engineering,



or production ML systemsProven experience building production batch and real‐time ML systemsExperience working closely with Data Scientists to productionize models and experimentation workflowsStrong experience building reusable tooling, frameworks, or internal developer platformsTechnical SkillsStrong Python and software engineering fundamentalsHands‐on experience with PyTorch and TensorFlow model deployment workflowsExperience with Docker, Kubernetes, and cloud‐native deployment patternsStrong CI/CD experience using GitHub Actions and cloud‐native CI/CD workflowsExperience with MLflow, model registry workflows, and multi‐environment promotionStrong understanding of API‐based inference services, async batch scoring, and event‐driven pipelinesSoft SkillsStrong collaboration with Data Scientists and product engineering teamsBuilder mindset with focus on developer experience and adoptionAbility to translate infrastructure complexity into simple self‐service workflowsPreferred QualificationsExperience building internal ML platforms from zero to first scaled adoptionExperience with feature stores and reusable feature access SDKsFamiliarity with Databricks, PySpark, Airflow, or equivalent orchestration toolingExperience with self‐service experimentation and A/B testing toolingExperience designing platform abstractions that maximize DS autonomy without compromising reliabilitySG is an Equal Opportunity Employer and does not discriminate against applicants due to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. #J-18808-Ljbffr

📌 Senior Machine Learning Engineer (Montreal)
🏢 Scientific Games
📍 Montreal