Staff ML Platform Engineer (MLOps)
New
F
FutureFit AISaaS/AI technology
Remote (US) / Remote (Canada)Full-TimeStaff
Salary172,000 USD - 220,000 CAD per year
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Job Details
- Required Skills
- PostgreSQLPythonSQLAirflowCI/CDdbtMLOps
Requirements
- Staff-level hands-on experience in MLOps, ML platform, or ML infrastructure.
- End-to-end MLOps practice deployment: CI/CD for models, experiment tracking, registries, and monitoring.
- Production experience with LLM-based systems: serving, evaluation, and cost/latency management.
- Proven experience operating both batch and real-time inference models.
- Expertise in compute provisioning, containerization, and managing frameworks in production environments.
- Track record of conducting controlled experiments like A/B tests and canary deploys.
- Strong depth in ML observability: drift detection, alerting, lineage, and prediction traceability.
- Ability to debug complex production incidents under pressure.
- Proficiency in data engineering, specifically feature computation, storage, and consistency.
- Strong systems design skills with the ability to translate product needs into durable architecture.
- Fluency in Python and SQL.
Responsibilities
- Evaluate current ML pipelines, data architecture, and workflows to create a prioritized optimization plan.
- Manage compute provisioning and maintain reproducible training and serving environments.
- Build infrastructure for LLM features, including cost-aware smart routing and quality evaluation.
- Implement production experimentation disciplines such as shadow deploys, canaries, and A/B testing.
- Develop observability tools for model monitoring, regression detection, and prediction traceability.
- Provide hands-on operational support, debugging and fixing production models during incidents.
- Handle necessary data engineering tasks for feature computation, storage, and consistency.
- Establish deployment and monitoring standards to foster shared ownership across the engineering team.
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