Senior Machine Learning Engineer Data Classification

Senior Machine Learning Engineer — Data Classification Location: United States — SF Bay Area preferred Engagement: Full-time commitment; initial three-month contract-to-hire Compensation: $110,000–$130,000 annualized, based on experience, paid monthly About Symosis Security Symosis Security is a Silicon Valley–based cybersecurity consulting firm helping enterprise and public-sector clients strengthen security through AI security, security engineering and automation, advisory, and managed security services. Our senior practitioners work directly with clients to solve complex problems and deliver measurable results. We’re expanding our AI and data security practice and looking for an experienced, hands-on ML engineer who wants technical ownership, direct client exposure, and opportunities to help grow the practice. About the Role You will build and improve sensitive-data classifiers for an enterprise client. Working alongside a technical lead and applied data scientist, you will translate error analysis into engineering improvements and deliver reliable, maintainable classification systems. This role requires strong coding skills and practical experience implementing and testing classifiers within existing enterprise frameworks. What You’ll Do 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. What You Bring 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. Preferred Experience 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. We prioritize demonstrated technical ownership and delivery over employer names. Compensation & Employment Structure Compensation is $110,000–$130,000 annualized , based on relevant experience and qualifications, paid monthly during the initial three-month contract period. Partial months will be prorated. The initial contract requires a full-time commitment and includes no company-provided employee benefits . Following a review of performance and ongoing business needs, the role may convert to permanent full-time employment with Symosis’s standard employee benefits. Compensation will be reviewed at conversion. Work must be performed within the United States, with availability for Pacific Time collaboration. SF Bay Area candidates are preferred; remote arrangements are subject to client approval. How to Apply Apply through LinkedIn and email your resume to View email address on click.appcast.io with the subject Senior ML Engineer — [Your Name] . Please include: Location: City/state and availability to collaborate during Pacific Time business hours. Start date: Earliest available start date and any notice period. Compensation: Confirmation that the posted compensation range and initial three-month contract-to-hire arrangement work for you. Relevant experience: A brief example of a classification system you personally built or improved, including your contribution and measurable results. Please do not share confidential client information.