ML and Data Engineer, Data Quality & PII Compliance
Posted on September 17, 2026 · Applications until October 18, 2026
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This remote ML and Data Engineer role involves designing validation suites, building adversarial test datasets for PII de-identification, and implementing automated regression gates. Candidates need over five years of experience in data engineering or machine learning, along with strong Python and SQL skills.
Description in English, as published by Turing.
About Turing
Turing is a leading AI company accelerating the advancement and deployment of frontier AI systems. We work with the world’s top AI labs and enterprises to improve capabilities in reasoning, coding, agentic behavior, multimodality, and other advanced AI domains.
About the Role
We are looking for an ML/Data Engineer to improve the quality, reliability, and compliance of enterprise data pipelines. You will focus on data quality validation and testing PII/PHI de-identification systems to ensure sanitized data is accurate, consistent, and free from sensitive information leaks.
This role combines data engineering, ML evaluation, test automation, and compliance-focused quality assurance.
What You’ll Do
- Design and automate validation suites for data pipelines, including schema checks, completeness validation, drift detection, and reconciliation across pipeline stages.
- Perform deep data quality analysis across enterprise data sources and connectors, including topic coherence, domain coverage, consistency, and depth.
- Build adversarial test datasets for PII/PHI de-identification systems, covering edge cases, obfuscated identifiers, multilingual entities, OCR noise, and unusual document formats.
- Evaluate NER and ML-based de-identification systems using precision, recall, F1 score, leak rates, and false-negative analysis.
- Identify and investigate PII leakage risks across raw, processed, and sanitized data.
- Implement automated regression gates in CI/CD to prevent pipeline changes from being deployed without passing data quality and privacy checks.
- Conduct sampling-based human-in-the-loop audits and maintain detailed audit trails for compliance evidence.
- Partner with data and engineering teams to perform root-cause analysis and resolve data inconsistencies, quality issues, and privacy leaks.
- Develop monitoring and reporting mechanisms for pipeline quality, de-identification performance, and compliance risks.
What We’re Looking For
- 5+ years of experience in data engineering, ML engineering, data quality, or a related field.
- Strong Python skills for test automation, data validation, and ML evaluation.
- Experience with testing frameworks and data-quality tools such as pytest, Great Expectations, Pandera, or similar.
- Strong SQL skills and experience validating data across multiple pipeline stages.
- Understanding of PII and PHI categories and de-identification concepts.
- Familiarity with privacy and compliance frameworks such as HIPAA Safe Harbor, GDPR, or LGPD.
- Experience evaluating NER or other ML-based systems using labeled datasets and precision/recall metrics.
- Ability to design reliable evaluations for non-deterministic ML or LLM-based systems.
- Experience integrating automated tests and quality checks into CI/CD pipelines.
- Familiarity with GCP services such as BigQuery, Google Cloud Storage, and Cloud Run Jobs.
- Strong analytical, debugging, and communication skills.
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: 40 hours per week with overlap of 6 hours per day with PST.
- Duration of Contract: 1 month (adjustable based on engagement)
Required skills
- Machine Learning
- Data Engineering
About Turing
Turing hires remote experts for AI and engineering projects, from software to medicine. The original posting is on their site.
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