Machine Learning Engineer

We are seeking an experienced Machine Learning Engineer to build, maintain, and scale end-to-end ML production pipelines. In this role, you will work closely with data teams and engineering leads to turn models into reliable, production-ready systems. You will focus on high-quality Python code development, robust containerization, and establishing best practices through active code reviews and knowledge sharing.

Key Responsibilities

• Production Deployment: Build, deploy, and maintain robust ML model pipelines in production environments.
• Code Engineering & Quality: Write clean, modular Python code and complex SQL queries. Lead and participate in rigorous code reviews to enforce software engineering best practices.
• Containerization & Infrastructure: Package, optimize, and containerize applications using Docker and enterprise base images like Universal Base Images (UBI).
• Collaboration & Knowledge Sharing: Work in an agile team environment, actively learning new frameworks while mentoring and sharing technical expertise with team members.

Required Qualifications

• Technical Stack:

• Advanced proficiency in Python and strong expertise in SQL.

• Hands-on experience containerizing applications with Docker and enterprise base images (UBI / Red Hat Base Images).

• Production ML Experience: Proven experience taking ML models out of research/notebook environments into scalable, secure production pipelines.

• Software Engineering Practices: Strong background in writing clean code, conducting thorough code reviews, and using CI/CD / Git workflows.

• Work Preference: Ability and willingness to work onsite 5 days a week at the San Antonio Home Office location.

Soft Skills & Attributes

• Strong problem-solving mindset and high attention to detail.
• Excellent attitude toward learning new tools and a passion for teaching/mentoring peers.
• Effective technical communication skills.