Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

We are seeking a Senior Machine Learning Engineer to build the foundational elements of our machine learning platform. The goal is to create self-service ML tooling and standardized workflows that empower Data Scientists to deploy models from experimentation to production for both batch and real-time applications. You will collaborate with senior engineers, Data Scientists, and stakeholders to establish reusable ML infrastructure, deployment processes, monitoring standards, and developer experience patterns.

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 their models in production.
Build foundational ML workflows including model registry, environment promotion, rollback, feature access patterns, 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, feature freshness, data quality, and business KPI monitoring.
Partner with Staff MLEs to shape the first-generation architecture of the ML platform.

Requirements

Master’s degree in Computer Science, Engineering, Machine Learning, Software Engineering, or another related STEM field.
Bachelor’s degree in a related STEM field with strong equivalent industry depth is also acceptable.
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.
Strong Python and software engineering fundamentals.
Hands-on experience with PyTorch and TensorFlow model deployment workflows.
Experience with Docker, Kubernetes, and cloud-native deployment patterns.
Strong CI/CD experience using GitHub Actions and cloud-native CI/CD workflows.
Experience with MLflow, model registry workflows, and multi-environment promotion.
Strong understanding of API-based inference services, async batch scoring, and event-driven pipelines.
Strong collaboration with Data Scientists and product engineering teams.
Builder mindset with focus on developer experience and adoption.
Ability to translate infrastructure complexity into simple self-service workflows.
Experience building internal ML platforms from zero to first scaled adoption.
Experience with feature stores and reusable feature access SDKs.
Familiarity with Databricks, PySpark, Airflow, or equivalent orchestration tooling.
Experience with self-service experimentation and A/B testing tooling.
Experience designing platform abstractions that maximize DS autonomy without compromising reliability.

Skills

Python
PyTorch
TensorFlow
Docker
Kubernetes
GitHub Actions
MLflow
API-based inference services
Async batch scoring
Event-driven pipelines
Feature stores
Databricks
PySpark
Airflow

Location

Toronto, ON

Work Type

Remote
Hybrid

Experience Level

Senior
3+ years

Education Level

Master’s degree in Computer Science, Engineering, Machine Learning, Software Engineering, or related STEM field
Bachelor’s degree in a related STEM field with strong equivalent industry depth

About the Company

Scientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries.
We offer cutting-edge backend systems, exciting entertainment experiences, and trailblazing retail and digital solutions.
We push game designs to the next level and are pioneers in data analytics and iLottery.
Our foundation is built on trusted partnerships, relentless innovation, legendary performance, and unwavering security.
We responsibly propel the global lottery industry ever forward.

Equal Opportunity

SG 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.
If you’d like more information about your equal employment opportunity rights as an applicant under the law, please click here for EEOC Poster.