Vercel Verified

Developer Tools, Cloud Computing, Web Hosting, SaaS

Machine Learning Engineer, Trust & Safety

San FranciscoHybridFull Time$208,000–$312,000 /yrPosted 29 days ago

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Required skills

production code
Python
JavaScript
TypeScript
Go
ML infrastructure
training pipelines
serving infrastructure
feature stores
evaluation tooling

Nice to have

open source ML tool
trust and safety
fraud prevention
abuse prevention

Role summary

We are seeking a Machine Learning Engineer for our Trust & Safety team to build and operate production systems for detecting and stopping platform abuse at internet scale. This role is 80% production code (services, pipelines, infrastructure) and 20% modeling, focusing on turning prototypes into hardened systems. Responsibilities include designing, building, and operating scalable and observable systems, maintaining ML infrastructure, and integrating LLMs and classical ML for abuse detection. The role requires 5+ years of software engineering experience with Python, and experience with ML infrastructure and LLM integration. Experience with JavaScript/TypeScript or Go, open-source ML tools, and trust/safety domains are preferred.

About Vercel:

Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience.

Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide.

About the role

We are looking for a Machine Learning Engineer on our Trust & Safety Engineering team to build and operate the production systems that detect and stop abuse on the platform at internet scale. This is an engineering-first role, roughly 80% writing and shipping production code (services, pipelines, and infrastructure) and 20% modeling, taking detection and classification approaches from prototype to hardened systems. This is a hybrid role based in San Francisco or New York City, with three days a week in the office.

What you’ll do

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

What you need

5+ years of software engineering experience building and operating production systems at scale

Wrote production code in Python, plus JavaScript/TypeScript or Go

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

Bonus if you

Built an open source ML tool

Worked in the trust and safety, fraud, or abuse prevention domain

Compensation & Benefits:

Competitive compensation package, including equity.

Inclusive Healthcare Package.

Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.

Flexible Time Off.

We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.

The San Francisco, CA base pay range for this role is $208,000.00 - $312,000.00. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process.

Disclosures:

Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data.

Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

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