Senior Machine Learning Engineer — Data Classification

Symosis Security is hiring a Senior Machine Learning Engineer to build and improve sensitive-data classifiers for an enterprise client. The role focuses on translating error analysis into tested engineering improvements, integrating reliable classification systems into the client’s existing framework, and delivering maintainable code and documentation.

Responsibilities:

• Build, configure, and improve rule-based and/or ML-based classifiers
• Develop and tune classification rules, features, thresholds, and supporting code
• Investigate false positives, missed detections, and coverage gaps
• Work with the data scientist to improve recall while maintaining precision
• Implement automated tests covering edge cases, regressions, and previously identified errors
• Run reproducible experiments and document code and configuration changes
• Integrate improvements into the client’s existing framework and development workflow
• Deliver maintainable code, technical documentation, and handoff materials
• Support client evaluation and an agreed remediation/retest cycle

Requirements:

• 5+ years of relevant ML or software engineering experience, including hands-on classification work
• Strong Python, SQL, Git, debugging, and automated testing skills
• Demonstrated experience personally building or improving classification systems
• Practical understanding of precision, recall, overfitting, data leakage, and validation
• Experience working within existing enterprise codebases and toolchains
• Ability to translate analytical findings into tested engineering changes
• Clear communication and effective collaboration with technical stakeholders
• Sensitive-data discovery, DLP, privacy engineering, security analytics, or content classification
• Pattern matching, regular expressions, feature engineering, and classifier threshold tuning
• Building reproducible evaluation workflows and regression test suites
• Classification systems operating at enterprise scale
• Prior experience at Google, Microsoft, Meta, Amazon, Apple, NVIDIA, Tesla, or a comparable technology organization
• SF Bay Area location