TuringCoding & software eval
ML and Data Engineer: Data Quality & PII Compliance
Pay not published
About this role, in Turing's words
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.
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.
Show all 9 itemsHide the other 6 in What you'll do
- 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.
Candidate background
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.
Quoted from selected sections of Turing's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Turing's words
Posted by Turing, reproduced here so you can judge the role before clicking. Original posting ↗
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)
Working with TuringPay, getting started and work, from Turing's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Paid monthly, around the 5th, straight to your bank account, or inside Deel on projects run through Deel. Its help articles disagree on whether that is the 5th calendar day or business day. help.turing.com/articles/9691407757-project-onboarding, help.turing.com/articles/6582454854-what-if-i-haven-t-rec..., help.turing.com/articles/1226770947-project-offboarding
- Before your first paid task
- A short application, with tests on some roles. Turing's review article says an interview is typically required for all roles. Onboarding covers the terms, ID verification with a driver's license or passport, and tax and payment details. help.turing.com/articles/2020987592-apply-for-jobs-at-turing, help.turing.com/articles/9179629201-how-long-does-the-app..., help.turing.com/articles/9691407757-project-onboarding
- How much work
- Review takes from 48 hours to 6 weeks after you finish applying, and the client makes the final choice. No reply within 6 weeks usually means you were not selected. help.turing.com/articles/9179629201-how-long-does-the-app..., help.turing.com/articles/2020987592-apply-for-jobs-at-turing
- Contract
- Depending on the project, the engagement rests on Turing's Terms of Service and a Service Agreement, on Deel, or on a partner that provides the contract. help.turing.com/articles/6582454854-what-if-i-haven-t-rec...
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Coding & software eval roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Turing's posting. How we count.
Pay across the field: Coding & software eval
Across 392 roles in this field with a stated hourly rate in US dollars, on 14 platforms, the middle half pays $65 to $120 an hour at the top of the range, and the median is $95.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr | 137 | $50 to $400 · median $100 |
| micro1 | 44 | $60 to $350 · median $120 |
| Handshake AI | 43 | $47 to $125 · median $80 |
| Meridial (Invisible) | 34 | $22 to $150 · median $60 |
| Mercor | 33 | $60 to $200 · median $105 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 19 Sep 2026, and still on Turing's list when we last read it on 13 Oct 2026.
- Posted by Turing
- First seen by AIPayList
- Last seen live
- Listing ID
- 107317
Turing posts this role once per country: 2 listings with the same title and pay. We treat them as one role, open in 0 countries.
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