Machine Learning / Data Engineer

📋 Description

• Design, train, and evaluate ML models that detect sensitive entities across text and image-based
• Build replacement pipelines that substitute detected entities with coherent alternatives at scale
• Run deep dives into enterprise data to assess quality
• Design and automate validation suites for data pipelines
• Surface and characterize quality issues for engineering and product
• Build adversarial test sets for de-identification across all sensitive data classes

🎯 Requirements

• 4-5 years of hands-on machine learning experience
• Strong Python for ML development and data validation (pytest, Great Expectations, Pandera)
• Solid SQL and experience validating data across pipeline stages
• Familiarity with sensitive data standards - HIPAA Safe Harbor, GDPR/LGPD, PCI DSS
• Experience building and testing NER or other ML-based detection systems
• Understanding of re-identification risk

🎁 Benefits

• Work at the frontier of AI
• Contribute to leading-edge AI research and showcase work at top conferences
• Bring frontier AI innovation to the enterprise
• Collaborate with exceptional colleagues from leading tech companies
• Move at the pace of AI innovation with startup speed and ownership