Trust & Safety ML Engineer: Production-Ready Abuse Detection

Vercel Inc.; San Francisco, New York (CA, NY); Hybrid; USD 208,000 - 312,000; Full time

Benefits offered by this job

WFH budget

Flexible Time Off

Mentorship & events

Equity included

Job summary

Vercel Inc. is seeking a Machine Learning Engineer for the Trust & Safety Engineering team. The role focuses on building and operating production ML systems to detect abuse at internet scale, with 80% production code and 20% modeling.

Hybrid role based in San Francisco or New York City, with three days a week in the office. Compensation includes equity and a WFH budget to outfit your space as needed.

Qualifications

• 5+ years of software engineering experience building and operating production systems at scale.
• Built and maintained ML infrastructure, such as training and serving pipelines, feature stores, or evaluation tooling.
• Integrated LLMs into production systems, including prompt engineering and evaluation.
• Built an open source ML tool.
• Worked in the trust and safety, fraud, or abuse prevention domain.

Responsibilities

• Design, build, and operate production systems that detect and disrupt abusive behavior across the platform, with an emphasis on reliability, scalability, and observability
• Build and maintain machine learning (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, turning prototypes into maintainable code
• Own systems end to end, from integrating a model into the platform through deployment, monitoring, and iteration
• Work with security, product, and infrastructure teams to turn abuse patterns and detection logic into production systems

Skills

Production systems

ML infrastructure

LLMs in production

Open source ML tool

Trust & Safety

Job description

Vercel Inc. is seeking a Machine Learning Engineer for the Trust & Safety Engineering team. The role focuses on building and operating production ML systems to detect abuse at internet scale, with 80% production code and 20% modeling.

Hybrid role based in San Francisco or New York City, with three days a week in the office. Compensation includes equity and a WFH budget to outfit your space as needed.