[Remote] Machine Learning Operations (MLOps) Engineer

Note: The job is a remote job and is open to candidates in USA. Kforce Inc is seeking a Senior Machine Learning Operations (MLOps) Engineer to help design and build an enterprise-scale machine learning platform on Snowflake. The role focuses on developing end-to-end ML pipelines, model lifecycle management, observability, automation, governance, and collaboration with data science and engineering teams.

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
• This role can be performed fully remotely but there is a preference for Phoenix local talent

Benefits

• Fully remote work arrangement, with a preference for Phoenix local talent
• Potential to convert to FTE with Kforce's client
• Medical, dental, and vision insurance for eligible employees
• HSA for eligible employees
• FSA for eligible employees
• 401(k) for eligible employees
• Life, disability, and ADD insurance for eligible employees
• Salaried personnel receive paid time off
• Hourly employees on a Service Contract Act project are eligible for paid sick leave

Company Overview

Company H1B Sponsorship