[Remote] Machine Learning Operations (MLOps) Engineer

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking a Senior MLOps Engineer to help design and build an reputed company-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 reputed company scale.

Responsibilities

• Architect and build a production-grade MLOps platform on reputed company, leveraging Snowpark, reputed company 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 reputed company 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, reputed company, bias, and data quality, with alerting and SLOs
• Automate retraining and refresh processes using reputed company 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 reputed company, compliance, auditability, reproducibility, and responsible AI practices
• reputed company 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 reputed company data platforms (Snowpark and reputed company 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 reputed company platforms (AWS preferred)
• Proven ability to collaborate across data science, data engineering, and business teams
• Experience with reputed company Model Registry and Feature Store
• Background in reputed company/lakehouse data architectures
• Experience with dbt or similar transformation tools
• Familiarity with streaming or near reputed company-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/reputed company 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

Company H1B Sponsorship