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.