Note: The job is a remote job and is open to candidates in USA. Zscaler provides a cloud security platform that protects customers from cyberattacks and data loss. The Senior Machine Learning Engineer will build AI- and machine-learning-driven solutions for customer risk identification, including agent logic, threat detection, data pipelines, and production deployment. The role also involves collaborating with threat research and data engineering teams while monitoring solution quality and reliability.
Responsibilities
- Translate risk identification methods into agent logic, understanding the benefits and limitations of agents, and how to ensure quality in different types of tasks, including risk analysis, explanations, and recommendations
- Collaborate closely with threat-research to understand data and threats and their approach to developing security heuristics
- Identify and solve data requirements for analysis, developing and collaborating with data engineering teams for pipelines, enrichments, and aggregations
- Follow a data-driven quality approach to threat-detection: including backtesting, balancing precision vs recall, tuning, and quality control
- Deploy and monitor your solutions in production in our CI/CD framework
Skills
- Experience building LLM-powered agents in production: tool and function calling, prompt and context engineering, multi-step orchestration frameworks (LangGraph, LangChain, or equivalent), and evaluation of non-deterministic output against ground truth
- 3+ years of professional Python development, with demonstrated ability to design and maintain production-quality systems with validated inputs, data contracts, and comprehensive unit and integration tests, alongside hands-on expertise with SQL and Python data analytics libraries (e.g., pandas, Polars, NumPy)
- Demonstrated ownership of production reliability: CI/CD, containerization, structured logging and metrics, observability and alerting, on-call participation, and incident debugging in a live distributed system, with familiarity with cloud and infrastructure-as-code in an AWS environment
- Senior-level ownership and leadership of projects, development, and testing
- Experience with production AI or ML systems where cost, latency, and accuracy are competing constraints, including handling model selection, routing, and regression testing
- Background in cyber threat research, threat modeling, threat hunting, detection engineering, or previous experience in data-driven risk analysis, fraud detection, adversary profiling and targeting, actuarial risk, or close collaboration with these types of teams to understand risk analysis and investigation processes
- Data engineering experience, including building and operating pipelines over large-volume event data: SQL, columnar or search-backed stores (OpenSearch/Elasticsearch, Athena/Presto, or similar), plus schema evolution, backfills, and data quality validation
Benefits
- Various health plans
- Time off plans for vacation and sick time
- Parental leave options
- Retirement options
- Education reimbursement
- In-office perks
Company Overview
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