Sglottery
Senior Machine Learning Engineer
Montreal, Canada · Senior
Sponsorship not specifiedDetected 5 days ago
PythonGitDatabricksDockerKubernetesCI/CDGitHub ActionsPlatform EngineeringMachine LearningTensorFlowPyTorchAirflowData AnalysisMLOpsA/B TestingCollaboration
About the role
- This role is not about creating a centralized gatekeeping team.
Responsibilities
- 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.
Requirements
- 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
- Experience working closely with Data Scientists to productionize models and experimentation workflows
- 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 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
- Required Qualifications
- Education
- Master's degree in Computer Science, Engineering, Machine Learning, Software Engineering, or another related STEM field
- Experience
Nice to have
- 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
- If you'd like more information about your equal employment opportunity rights as an applicant under the law, please click here for EEOC Poster.
Skills
- 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
Benefits
- We are looking for a Senior Machine Learning Engineer to help build the foundations of our machine learning platform from the ground up.
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This listing is sourced directly from Sglottery's careers page and normalized into a canonical job model.