Machine Learning / Data Engineer
Turing · Engineering · Senior · 1mo ago
Open to candidates living in Brazil, Colombia.
Direct from the employer's own careers page
Who can apply
Read straight from the listing, so you know before you spend time on it.
Open to candidates living in Brazil, Colombia.
“This is a full-time remote role based in Brazil or Colombia.”
- Async-first
- The listing doesn't promise async-first working.
- Contractor / B2B
- No mention of hiring international contractors or invoicing.
- Global stipend
- No home office or equipment budget mentioned.
- Annual retreat
- No company-paid get-togethers mentioned.
Read from the listing automatically. Always confirm the details with the company before you accept an offer.
About the role
This is a hands-on individual contributor role focused on building ML models and validation infrastructure to ensure data quality and sanitization. You will develop NER-based and image-based detection pipelines, create replacement systems for sensitive information (PII, PHI, CII, and financial data), and design adversarial test sets to maintain strict compliance without downstream re-identification risks.
What you'll do
- Run deep dives into enterprise data to evaluate topic coherence, domain depth, completeness, and consistency across connectors.
- Design and automate pipeline validation suites for schema checks, drift detection, and data reconciliation.
- Train and evaluate machine learning models (NER and document-level detectors) to identify sensitive entities across text and images.
- Build robust replacement pipelines to substitute sensitive entities consistently across file corpuses.
- Develop adversarial test suites covering edge cases, obfuscated identifiers, and OCR noise to stress-test de-identification systems.
- Implement regression gates in CI/CD and manage human-in-the-loop sampling audits to ensure compliance and prevent data leaks.
What you bring
- 4 to 5 years of hands-on machine learning experience with ML as your core background.
- Strong Python skills for ML engineering and data validation (pytest, Great Expectations, Pandera, or similar).
- Solid SQL experience validating data flows across multi-stage pipelines.
- Familiarity with compliance standards including HIPAA Safe Harbor, GDPR/LGPD, and PCI DSS.
- Proven experience building and evaluating NER systems, adversarial test sets, and entity replacement strategies.
- Strong understanding of re-identification risk and a detail-oriented, QA-driven mindset.
About Turing
Turing accelerates AI development by building high-quality datasets, reinforcement learning environments, and frontier benchmarks in partnership with leading AI labs and Fortune 500 enterprises. Headquartered in San Francisco, the company deploys end-to-end agentic systems across critical enterprise workflows.
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