MLOps Platform Engineer Snowflake || Remote

Job Title: MLOps Platform Engineer Snowflake

Location: Remote
Job Type: Contract W2 / C2C / 1099
Experience: 5+ Years

Job Overview

We are seeking an experienced MLOps / ML Platform Engineer to design, build, operate, and continuously mature an end-to-end ML production ecosystem on Snowflake.

This is a unique greenfield opportunity to build the platform from the ground up using Snowpark, Snowflake ML, Model Registry, and Feature Store capabilities.

The platform will be built on an enterprise Medallion Architecture (Bronze, Silver, Gold), enabling ML models to consume curated, governed, high-quality data products with strong lineage, scalability, and operational reliability.

Key Responsibilities

• Architect and build a production-grade MLOps platform on Snowflake using Snowpark and Snowflake-native ML capabilities.
• Design reusable ML pipelines covering training, validation, deployment, inference, and monitoring.
• Build MLOps workflows aligned with Bronze, Silver, and Gold data layers.
• Establish model lifecycle management standards including versioning, approval workflows, promotion gates, rollback strategies, and model lineage.
• Partner with Data Scientists to productionize ML models efficiently and safely.
• Implement model observability covering model performance, drift, bias, data quality, and service reliability.
• Create actionable monitoring, alerting, and SLO frameworks.
• Automate model retraining and refresh workflows using Snowflake Tasks, Dynamic Tables, and event-driven orchestration.
• Partner with Data Engineering teams to ensure feature pipelines are reliable, reusable, and synchronized with medallion-layer evolution.
• Define and implement CI/CD pipelines for ML code, data, models, and configuration.
• Establish testing frameworks and release controls for production ML workflows.
• Drive MLOps governance across security, compliance, auditability, reproducibility, and responsible AI.
• Lead platform maturation from MVP to enterprise scale.
• Create technical documentation, developer enablement materials, and operational runbooks.

Required Qualifications

• 5+ years of experience in ML Engineering, MLOps, Machine Learning Platform Engineering, or related roles.
• Strong Python and SQL skills with experience building production ML pipelines.
• Hands-on experience with Snowflake data and compute capabilities.
• Experience with Snowpark and/or Snowflake-native ML tooling strongly preferred.
• Proven experience with model deployment, versioning, monitoring, and lifecycle management in production.
• Experience implementing CI/CD and automated testing strategies for ML systems.
• Strong understanding of feature engineering, training-serving consistency, and data quality controls.
• Experience with cloud infrastructure and services; AWS preferred.
• Strong communication and collaboration skills with the ability to work across Data Science, Data Engineering, and business teams.

Preferred Qualifications

• Experience with Snowflake Model Registry.
• Experience with Snowflake Feature Store.
• Experience implementing model observability within Snowflake.
• Experience designing ML systems using Medallion / Lakehouse architectures.
• Experience with dbt or similar data transformation frameworks.
• Familiarity with streaming or near-real-time inference patterns.
• Experience in high-volume operational domains such as logistics, fleet management, route optimization, or environmental services.
• Previous experience building greenfield ML/MLOps platforms and defining engineering and operating standards from the ground up.

Key Technologies

Snowflake | Snowpark | Snowflake ML | Model Registry | Feature Store | Python | SQL | AWS | CI/CD | MLOps | ML Pipelines | Medallion Architecture | dbt | Model Monitoring | Feature Engineering

Thanks

Navya