Dockerfile Data Validation Engineer
Veröffentlicht am 24. November 2025 · Bewerbung bis 15. November 2026
Einige Länder: Lateinamerika, Naher Osten und Nordafrika, Subsahara-Afrika, Südasien
Ich leite Sie zur offiziellen Seite von Turing weiter. Die Bewerbung ist kostenlos und auf Englisch.
Ich erhalte von der Plattform eine Provision, wenn ein von mir empfohlener Kandidat eingestellt wird. Für Sie ändert sich nichts.
This remote role involves designing and maintaining data validation workflows inside Docker based build pipelines. The candidate must have four plus years of DevOps experience with strong Docker skills and proficiency in Python or Bash.
Beschreibung auf Englisch, wie von Turing veröffentlicht.
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 with 4+ years of experience
- 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]
- Location : India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico, Brazil
Evaluation Process (approximately 75 mins) :
- Interviews (30-60 min technical discussion in QODE)
Erforderliche Fähigkeiten
- Python
- Bash
- Docker
- CI/CD
Einige Länder: Lateinamerika, Naher Osten und Nordafrika, Subsahara-Afrika, Südasien
Über Turing
Turing stellt Remote-Experten für KI- und Engineering-Projekte ein, von Software bis Medizin. Die Originalanzeige steht auf deren Website.
Diese Stelle auf Turing ansehenÄhnliche Stellen
Senior Software Engineer, Python (LLM Evaluation & Repository Validation)
This remote role involves analyzing GitHub issues, setting up development environments with Docker, and evaluating test quality to build LLM training datasets. Candidates must have at least three years of experience, strong Python skills, and proficiency with Git and Docker.
- Python
Vor 469 Tagen veröffentlicht
SWE Bench, Data Engineer/Data Scientist
This remote role involves designing data pipelines, processing real-world datasets, and supporting benchmark-driven evaluation projects for advanced AI systems. Candidates need at least three years of professional experience as a data engineer, data scientist, or software engineer, alongside strong Python proficiency.
- Data Engineering
- Data Science
Vor 261 Tagen veröffentlicht
Software Engineer, AI Code Evaluation & Benchmarking (US candidates only)
This remote contractor role involves reviewing AI-generated code, validating software engineering solutions, and building evaluation datasets. Candidates need a computer science degree, over three years of professional software engineering experience, and strong programming proficiency.
- Python
- Git
- Docker
Vor 125 Tagen veröffentlicht
Senior Software Engineer für LLM Evaluation & Repository Validation
Der Senior Software Engineer analysiert GitHub-Issues, richtet Entwicklungsumgebungen ein und bewertet die Testabdeckung, um verifizierbare Software-Engineering-Aufgaben für Large Language Models zu entwickeln. Kandidaten müssen über fundierte Erfahrung in einer gängigen Programmiersprache sowie Kenntnisse in Git, Docker und Pipeline-Einrichtung verfügen.
- Python
- JavaScript
- Java
- +5
Vor 519 Tagen veröffentlicht
