Overview
Senior Staff Machine Learning Engineer on the AI Platform and Data Science team, focused on high-fidelity risk identification in customer data. 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 ensuring quality across risk analysis, explanations, and recommendations
- Collaborate closely with threat-research to understand data, 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 within our 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
- 8+ 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
- 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, incident debugging in live distributed systems
- Familiarity with cloud and infrastructure-as-code in an AWS environment
- Sr. Staff level ownership and leadership of emergent requirements, architecture, and complex engineering projects
Nice to have
- 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 risk analysis teams
- Data engineering experience building and operating pipelines over large-volume event data using SQL, columnar or search-backed stores (OpenSearch/Elasticsearch, Athena/Presto), schema evolution, backfills, and data quality validation
Details
- Remote (USA) role; location line also lists Santa Clara, California, USA
- Full-time position
- Base pay range $157,500 to $225,000 USD (excludes commission, bonus, equity and benefits)
Read the full description and apply on the company’s own careers page.