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Salary: USD 208,000 - 312,000 / annual
Vercel is seeking a Machine Learning Engineer for its Trust & Safety Engineering team to build and operate production systems that detect and prevent abuse on the platform at internet scale. This is an engineering-focused role where you'll spend approximately 80% of your time writing and shipping production code (services, pipelines, infrastructure) and 20% on ML modeling, taking detection and classification approaches from prototype to hardened systems.
Key responsibilities include:
- Design, build, and operate production systems that detect and disrupt abusive behavior across the platform, with emphasis on reliability, scalability, and observability
- Build and maintain ML infrastructure including training pipelines, feature pipelines, serving infrastructure, and evaluation frameworks
- Ship large language model (LLM) and classical ML approaches for abuse detection and classification, converting prototypes into maintainable production code
- Own systems end-to-end, from model integration through deployment, monitoring, and iteration
- Collaborate with security, product, and infrastructure teams to translate abuse patterns and detection logic into production systems
The role is hybrid based in San Francisco or New York City, requiring three days per week in the office.
Requirements:
- 5+ years of software engineering experience building and operating production systems at scale
- Production code experience in Python, plus JavaScript/TypeScript or Go
- Experience building and maintaining ML infrastructure such as training and serving pipelines, feature stores, or evaluation tooling
- Experience integrating LLMs into production systems, including prompt engineering and evaluation
Bonus qualifications:
- Built an open source ML tool
- Worked in trust and safety, fraud, or abuse prevention domain
