Machine Learning Engineer, Trust & Safety
$208k - $312k • Hybrid - San Francisco, New York City
Posted 9d ago
Job Location
Hybrid - San Francisco, New York City
Tech Stack
Remote Work Policy
On-site
Categories
Machine Learning Engineer
About the job
Vercel is seeking a Machine Learning Engineer for its Trust & Safety Engineering team. This role focuses on building and operating production systems to detect and prevent platform abuse at scale. It's an engineering-intensive position, with approximately 80% of the time dedicated to writing and deploying production code, including services, pipelines, and infrastructure, and 20% focused on modeling. The goal is to take detection and classification approaches from initial prototypes to robust, production-ready systems.
Responsibilities
- Design, build, and operate production systems for detecting and disrupting abusive behavior, prioritizing reliability, scalability, and observability.
- Develop and maintain ML infrastructure, including training pipelines, feature pipelines, serving infrastructure, and evaluation frameworks.
- Implement LLM and classical ML methods for abuse detection and classification, converting prototypes into maintainable code.
- Manage systems end-to-end, from model integration and deployment to monitoring and iteration.
- Collaborate with security, product, and infrastructure teams to translate abuse patterns and detection logic into production systems.
Requirements
- 5+ years of software engineering experience building and operating production systems at scale.
- Proficiency in Python for production code development.
- Experience with JavaScript/TypeScript or Go.
- Experience building and maintaining ML infrastructure (e.g., training/serving pipelines, feature stores, evaluation tooling).
- Experience integrating LLMs into production systems, including prompt engineering and evaluation.
Benefits
- Competitive compensation package including equity.
- Inclusive Healthcare Package.
- Mentorship and opportunities to attend events for networking and skill development.
- Flexible Time Off.
- Provision of necessary gear and a WFH budget.