Machine Learning Engineer

Hello ,

We have an exciting opportunity for an experienced Machine Learning Engineer with strong expertise in ML model production pipelines, Python programming, SQL, code reviews, and Docker-based environments.

Pay rate

$56/hr w2

Job Details

• Job Title: Machine Learning Engineer – Production Pipelines
• Visa: USC/GC
• Location: San Antonio, Texas
• Work Mode: Onsite – San Antonio Home Office
• Availability Requirement: 5 days per week onsite
• Mandatory Skills: ML Model Production Pipelines, Python, SQL, Code Reviews, Docker, Universal Base Images
• Key Competencies: Collaboration, Continuous Learning, Knowledge Sharing

Job Summary

We are seeking a motivated Machine Learning Engineer to support the development, deployment, and maintenance of production-ready machine learning pipelines. The ideal candidate will have strong Python coding skills, SQL expertise, experience with Docker and Universal Base Images, and the ability to review code and contribute to reliable ML production workflows.

The candidate should demonstrate a willingness to learn new technologies, share knowledge, and collaborate effectively with the team to improve engineering practices and production readiness.

Key Responsibilities

• Develop, maintain, and optimize machine learning model production pipelines.
• Write clean, efficient, and maintainable Python code.
• Use SQL to retrieve, process, and validate data for ML workflows.
• Participate in code reviews and follow established coding standards.
• Build and manage containerized applications using Docker.
• Work with Universal Base Images to support secure and consistent container environments.
• Support deployment, testing, troubleshooting, and maintenance of production ML pipelines.
• Collaborate with team members to improve pipeline reliability and operational efficiency.
• Share technical knowledge, learn new tools and technologies, and contribute to continuous improvement.

Required Skills and Qualifications

• Hands-on experience with machine learning model production pipelines.
• Strong Python programming and coding skills.
• Proficiency in SQL.
• Experience conducting and participating in code reviews.
• Working knowledge of Docker and containerization.
• Familiarity with Universal Base Images.
• Strong problem-solving and troubleshooting abilities.
• Positive attitude toward continuous learning, mentoring, and knowledge sharing.
• Ability to work onsite five days per week at the San Antonio home office.

Key Competencies

• ML Model Deployment and Production Pipelines
• Python Development
• SQL and Data Processing
• Code Quality and Review
• Docker and Containerization
• Universal Base Images
• Team Collaboration and Knowledge Sharing
• Continuous Learning and Improvement