Dockerfile Data Validation Engineer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI hires and contracts contributors for specialized projects, helping you build a credible profile, discover relevant opportunities, and grow a long-term portfolio in a fast-moving technology field.

Creating an OpenTrain account is free, and candidates apply through OpenTrain for roles that match their skills and experience.

• Contractor and part-time engagement
• Open to candidates in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Türkiye, Mexico, and Brazil
• English-language role
• Time requirement of 20+ hours per week

About AI Training and Data Validation Work

AI systems depend on carefully prepared, checked, and documented data. In technical AI-training projects, engineers help make sure datasets, schemas, metadata, and model artifacts are reliable before they move through development or deployment workflows.

This role contributes to the infrastructure behind AI work by combining containerization, scripting, automated quality controls, and reproducible builds. It is an opportunity to support cutting-edge AI systems through dependable data and software practices.

• Work on the technical systems that support modern AI development
• Help improve data quality, reproducibility, and deployment readiness
• Apply DevOps and validation expertise to AI-focused workflows

The Role

OpenTrain is recruiting a Dockerfile Data Validation Engineer to build and maintain validation workflows inside Docker-based build pipelines supporting advanced AI systems. You will help ensure datasets, schemas, and model artifacts meet quality and compliance requirements before deployment.

The role focuses on reliable, reproducible, and fully validated containerized data pipelines. You will combine Docker configuration, metadata standards, scripting, and automated quality controls while collaborating across data engineering, machine learning, and DevOps workflows.

• Subject area: containerized data validation pipeline engineering
• Listed experience level: entry level
• Required professional background: at least four years of DevOps experience
• Primary language: English

What You'll Do

You will develop validation processes that run as part of containerized builds and help make data-quality failures visible before deployment. Your work will cover Dockerfile configuration, metadata, scripts, CI/CD integration, and documentation.

• Develop and optimize Dockerfiles with built-in data-validation steps
• Implement Docker LABEL metadata for dataset versions, schemas, and lineage
• Create Python or Bash scripts for schema checks, data integrity, and quality control
• Integrate validation into CI/CD pipelines
• Enforce fail-on-bad-data checks
• Document Dockerfile labeling, validation logic, and data-governance standards
• Collaborate across data engineering, machine learning, and DevOps workflows

Required Skills and Experience

This role requires strong practical experience with Docker-based development and DevOps workflows. You should be comfortable writing validation scripts, working with structured data requirements, and integrating automated checks into build and deployment systems.

• At least four years of DevOps experience
• Strong experience designing and optimizing Dockerfiles
• Proficiency with Python or Bash for validation scripting
• Knowledge of data formats, schemas, and validation tools
• Experience integrating checks into CI/CD systems
• Familiarity with container registries
• Understanding of metadata, data lineage, and reproducible builds

Helpful Background

The following experience is helpful for this project but is not listed as required. It may be especially relevant if you have worked on AI development infrastructure or automated engineering workflows.

• LLM research or evaluation
• Developer tools
• Automation agents
• MLOps workflows
• Data versioning
• Great Expectations
• Kubernetes
• Container security

Why Work With OpenTrain

AI training and data-labeling work is one of the fastest-growing ways to work in technology. Contributors help shape how AI systems behave, and technical specialists can bring valuable software, infrastructure, and data-quality expertise to this expanding field.

OpenTrain gives you a place to build a profile around your AI-training and data-labeling experience, discover projects aligned with your skills, and develop a durable freelance portfolio instead of starting from scratch for every opportunity.

• Access specialized AI-training opportunities in one place
• Build a profile that reflects your technical experience
• Find flexible part-time contractor work
• Grow experience in a rapidly developing AI industry
• Apply in minutes through OpenTrain