[Hiring] Senior Machine Learning Engineer @Zscaler

Role Description

We are looking for a Senior Machine Learning Engineer to join our team. This is a remote (USA) role, reporting to the Manager AI Platform and Data Science in the AI Platform and Data Science department. This team’s mission is high-fidelity risk identification in customer data. Our goals are to catch all threats while minimizing noise. To do this, you will develop solutions applying data analysis and threat-research, while using AI, machine learning, and data engineering to build quality, data-driven components to automate security analysis.

What you’ll do (Role Expectations)

• 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.

Who You Are (Success Profile)

• You thrive in ambiguity and are comfortable building the path as you walk it, viewing unstructured dynamic environments as raw material to create meaningful solutions.
• You act like an owner with a deep passion for the mission, navigating seamlessly between high-level strategy and hands-on execution to drive outcomes with integrity.
• You possess a true growth mindset, continuously developing your skills and actively seeking feedback to become a stronger partner and impact-driven teammate.
• You serve as a positive force, approaching complex technical challenges with contagious constructive energy that inspires your team to stay solution-focused.
• You are relentlessly data-driven, leveraging analytics and empirical evidence over assumptions to measure what matters and guide informed decisions.

What We’re Looking for (Minimum Qualifications)

• 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.

What Will Make You Stand Out (Preferred Qualifications)

• 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, and more!