Senior Machine Learning Engineer

Overview

Senior Machine Learning Engineer on the AI Platform and Data Science team, focused on high-fidelity risk identification in customer data: catching all threats while minimizing noise. Remote (USA) role reporting to the Manager AI Platform and Data Science.

What you'll do

• Translate risk identification methods into agent logic, understanding the benefits and limitations of agents, and how to ensure quality across 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 solutions in production in the CI/CD framework.

What you'll need

• 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 ability to design and maintain production-quality systems with validated inputs, data contracts, and comprehensive unit and integration tests.
• 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.
• Familiarity with cloud and infrastructure-as-code in an AWS environment.
• Senior-level ownership and leadership of projects, development, and testing.

Nice to have

• Experience with production AI or ML systems where cost, latency, and accuracy are competing constraints, including model selection, routing, and regression testing.
• Background in cyber threat research, threat modeling, threat hunting, detection engineering, or data-driven risk analysis, fraud detection, adversary profiling and targeting, actuarial risk, or close collaboration with these 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.

Details

• Remote (USA) role; location line lists Remote - USA and Santa Clara, California, USA.
• Full-time position.
• Base pay range $115,500 – $165,000 USD (excludes commission, bonus, equity, and benefits).