Dockerfile Data Validation Engineer - 52945

About Turing: Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.About the Role: We are seeking an engineer responsible for designing, implementing, and maintaining data-validation workflows inside Docker-based build pipelines. This role involves creating and managing Dockerfile labels, metadata standards, and validation scripts that ensure datasets, schemas, and model artifacts meet quality and compliance requirements before deployment.You will work closely with data engineering, machine learning, and DevOps teams to build reliable, reproducible, and fully validated containerized data pipelines.What does day-to-day look like:Develop and optimize Dockerfiles with built-in data-validation steps.Implement LABEL metadata for dataset versions, schemas, and lineage.Create validation scripts (Python/Bash) for schema checks, data integrity, and quality control.Integrate validation steps into CI/CD pipelines and enforce fail-on-bad-data checks.Document standards for Dockerfile labeling, validation logic, and data governance.Required Skills:Experienced DevOps engineers.Strong experience with Docker & Dockerfiles.Proficiency in Python or Bash for validation scripting.Knowledge of data formats, schemas, and validation tools.Familiarity with CI/CD systems and container registries.Nice to Have:Previous participation in LLM research or evaluation projects.Experience building or testing developer tools or automation agents.Experience with MLOps workflows, data versioning, or Great Expectations.Knowledge of Kubernetes or container security tools.Perks of Freelancing With Turing:Work in a fully remote environment.Opportunity to work on cutting-edge AI projects with leading LLM companies.Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)Employment type : Contractor assignment (no medical/paid leave)Duration of contract : 2-4 weeks; [expected start date is next week]Evaluation Process (approximately 75 mins) :Interviews (30-60 min technical discussion in QODE)Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.