Senior Machine Learning Engineer
Job Summary
As a Senior Machine Learning Engineer, you will own the core ML detection platform that identifies account compromise in real time. You will build and evolve detection models, take them from research to production at scale, and work directly with customers to understand emerging threats. This high-impact role on a lean, high-caliber team lets you shape technical direction while architecting systems that handle rapid growth.
Essential Functions
- Design, build, and evolve detection models that identify account compromise in real time
- Take machine learning models from research and training through to production deployment at scale
- Architect scalable ML systems capable of handling 10-100x growth in data volume and complexity
- Collaborate with leadership and cross-functional teams to understand customer threats and identify new detection signals
- Establish engineering patterns, raise technical standards, and drive quality across the ML platform
- Own systems end-to-end, including infrastructure, monitoring, and performance at scale
Required Qualifications
- 4+ years of machine learning engineering experience with meaningful production model deployments at scale
- Strong quantitative fundamentals including probability and statistics, linear algebra, anomaly detection, behavioral modeling, and NLP
- Experience taking ML models end-to-end from training to production in high-scale environments
- Production-grade Python coding skills and end-to-end system design ability
- Hands-on experience with real-time or streaming data pipelines, feature stores, distributed systems, and high-performance databases
- BS or higher in Computer Science, Mathematics, Statistics, or a related quantitative field
- Demonstrated high agency with ability to scope and execute work independently
Preferred Qualifications
- Background in quantitative finance, fraud detection, or other high-stakes domains
- First-author publication at a top ML conference such as NeurIPS, ICML, or ICLR
- Experience at reputable ML organizations or in environments with similar technical rigor
- Familiarity with Node.js, TypeScript, or React in full-stack contexts
Technical Skills
- Python
- Machine Learning
- NLP
- Anomaly Detection
- Real-time Data Pipelines
- Distributed Systems
- High-Performance Databases
- Streaming Infrastructure
- Quantitative Modeling
- System Design at Scale
Education & Certifications
BS or higher in Computer Science, Mathematics, Statistics, or another quantitative field. First-author publication at a top ML conference is preferred.
Compensation & Benefits
Total compensation range is $250,000 - $300,000, which includes base salary, equity, and performance bonuses. Benefits include comprehensive medical, dental, and vision coverage, unlimited PTO, learning stipend, and meaningful equity in a high-growth company.