Senior Machine Learning Engineer

LotusLynx; Pittsburgh (Allegheny County); On-site; USD 120,000 - 150,000; Full time

Job summary

LotusLynx is seeking a Senior or Lead MLOps Engineer to bolster enterprise machine learning platforms. This role involves designing and deploying scalable machine learning infrastructure and MLOps workflows, working closely with Data Science, Platform Engineering, and Software Engineering teams.

The ideal candidate will have over 6 years of experience in MLOps or Machine Learning Engineering and strong skills in Python, SQL, and more. This collaborative position seeks professionals comfortable driving AI initiatives in production environments.

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.
• Strong experience with Python, SQL, Spark, Hive, Linux, Git, and OpenShift.

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.
• Mentor junior engineers and share technical expertise across the team.

Skills

Python

SQL

Spark

Hive

Git

OpenShift

CI/CD Automation

Distributed Data Processing

Infrastructure Automation

Production Support and Troubleshooting

Education

6+ years experience in MLOps or related fields

Job description

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

Required Technical Skills

Core Technologies

• Python
• SQL
• Spark
• Hive
• Git
• OpenShift
• CI/CD Automation
• Distributed Data Processing
• Infrastructure Automation
• Production Support and Troubleshooting

Additional Experience

• 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
• 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
• 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.