Senior/Lead MLOps Engineer

Please note: 2 openings-one SR MLOps Engineer and one Lead MLOps Engineer. Both roles are direct hire on w2. Client is open to relocation candidates who are currently based in the US. NO c2c, third parties, or 1099 here.

Position Overview

We are seeking a Senior or Lead MLOps Engineer to support enterprise machine learning platforms and production AI initiatives. This role will focus on designing, deploying, optimizing, and supporting scalable machine learning infrastructure, feature pipelines, and MLOps workflows that power advanced analytics and AI solutions.

Depending on experience, candidates may enter at either the Senior or Lead level. The ideal candidate will bring hands-on experience supporting machine learning solutions in production environments and possess strong expertise in MLOps, distributed data processing, automation, and platform engineering.

This is a highly collaborative role partnering closely with Data Science, Platform Engineering, and Software Engineering teams.

Key Responsibilities

• Design, develop, and support production MLOps pipelines and machine learning infrastructure
• Build and optimize scalable batch and real-time data and feature pipelines
• Deploy, monitor, and support machine learning models in production environments
• Partner with Data Scientists to operationalize machine learning solutions
• Develop automation, CI/CD processes, monitoring, and observability frameworks
• Troubleshoot and resolve complex production issues
• Improve machine learning lifecycle management, governance, and operational efficiency
• Contribute to platform architecture, engineering standards, and best practices
• Mentor junior engineers and share technical expertise across the team

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• Lead technical initiatives and provide technical guidance based on experience level

Required Technical Skills:

Core Technologies

• Python
• SQL
• Spark
• Hive
• Linux
• Git
• OpenShift

MLOps & Platform Engineering

• Production MLOps Pipelines
• Machine Learning Model Deployment

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• Model Monitoring
• CI/CD Automation
• Distributed Data Processing
• Infrastructure Automation
• Production Support and Troubleshooting

Additional Experience

• Machine Learning Platforms
• Platform Reliability
• Monitoring and Observability
• Enterprise AI Solutions

Qualifications:

• 6+ years of experience in MLOps, Machine Learning Engineering, Data Engineering, ML Platform Engineering, or related disciplines
• Demonstrated experience supporting machine learning models in production environments

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• Strong experience with Python, SQL, Spark, Hive, Linux, Git, and OpenShift
• Experience working directly with Data Science and Machine Learning teams
• Strong communication and collaboration skills
• Ability to work effectively in a highly visible, team-oriented environment

Preferred Experience:

• Technical leadership, mentoring, or lead engineering responsibilities
• Kubernetes
• Cloud Platforms (AWS, Azure, or GCP)
• Enterprise AI and Machine Learning Platforms
• Experience influencing architecture and engineering standards

What We're Looking For:

We are seeking experienced engineers who have successfully deployed and supported machine learning solutions in production environments. This is not an entry-level MLOps opportunity. Candidates should be comfortable contributing immediately, collaborating across teams, and helping drive scalable AI and machine learning initiatives.