Note: The job is a remote job and is open to candidates in USA. Kforce Inc is seeking a Senior MLOps Engineer to help design and build an enterprise-scale machine learning platform from the ground up. This role will play a key part in shaping standards, processes, and tooling as the platform evolves from MVP to enterprise scale.
Responsibilities
- Architect and build a production-grade MLOps platform on Snowflake, leveraging Snowpark, Snowflake ML, Model Registry, and Feature Store
- Design and operationalize reusable pipelines for training, validation, deployment, inference, and monitoring
- Align ML workflows with Bronze, Silver, and Gold medallion layers to ensure consistent use of trusted data
- Establish model lifecycle management standards, including versioning, approvals, promotion gates, and rollback strategies
- Partner with data scientists to productionize models into scalable, reliable services
- Implement model observability for performance, drift, bias, and data quality, with alerting and SLOs
- Automate retraining and refresh processes using Snowflake Tasks, Dynamic Tables, and event-driven orchestration
- Collaborate with data engineering teams to ensure reliable and reusable feature pipelines
- Define and implement CI/CD pipelines for ML systems, including testing frameworks and release controls
- Drive governance across security, compliance, auditability, reproducibility, and responsible AI practices
- Lead platform maturation, including documentation, developer enablement, and operational runbooks
Skills
- 5+ years of experience in ML Engineering, MLOps, or platform engineering
- Strong Python and SQL skills, with experience building production ML pipelines
- Hands-on experience with Snowflake data platforms (Snowpark and Snowflake ML strongly preferred)
- Experience with model deployment, versioning, monitoring, and lifecycle governance
- Experience implementing CI/CD and testing strategies for ML systems
- Strong understanding of feature engineering, training-serving consistency, and data quality controls
- Experience working with cloud platforms (AWS preferred)
- Proven ability to collaborate across data science, data engineering, and business teams
- Experience with Snowflake Model Registry and Feature Store
- Background in medallion/lakehouse data architectures
- Experience with dbt or similar transformation tools
- Familiarity with streaming or near real-time ML inference
- Experience in high-volume operational environments (e.g., logistics, fleet, routing)
- Prior experience building greenfield platforms and establishing standards from scratch
Benefits
- Medical/dental/vision insurance
- HSA
- FSA
- 401(k)
- Life, disability & ADD insurance to eligible employees
- Paid time off for salaried personnel
- Paid sick leave for hourly employees on a Service Contract Act project
Company Overview
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