Machine Learning Engineer, Trust & Safety
This listing is for a Machine Learning Engineer, Trust & Safety role at Vercel, in Hybrid - San Francisco, New York City, United States. It is listed as a full-time position with hybrid working.
DGJ summary of this job
Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.
This listing is for a Machine Learning Engineer, Trust & Safety role at Vercel, in Hybrid - San Francisco, New York City, United States. It is listed as a full-time position with hybrid working.
Reading the advert, the employer asks for 5+ years of experience.
Skills and tools named in the text include Python, JavaScript, TypeScript, machine learning, LLM and observability.
The listing gives the pay as $208,000.00 - $312,000.00.
Benefits mentioned in the advert: bonus.
The advert does not mention visa sponsorship. If you would move to United States for this job, check the official work permit route first (DGJ Insight lists it where we have it).
Dev Global Jobs found this job on Greenhouse on Nov 8, 2026.
- Employer
- Vercel
- Location
- Hybrid - San Francisco, New York City, United States
- Work mode
- hybrid
- Job type
- Full-time
- Pay
- $208,000.00 - $312,000.00
- Experience asked
- 5+ years
- Found
- Nov 8, 2026 on Greenhouse
- Employer text
- 536 words, about 2 min to read
- Apply only on the official page (job-boards.greenhouse.io). Dev Global Jobs is not the employer and never asks for a fee.
- Compare your own experience with the 5+ years the advert asks for, and show it clearly near the top of your CV.
- Mirror the skills the advert names (Python, JavaScript, TypeScript and machine learning) in your CV where you really have them; applicant tracking systems look for these words.
- Read the employer’s full text below (about 2 min) before you apply.
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DGJ Insight
Our own data about this role and place, from official statistics and our live job index.
This job's listed pay is 199% above the benchmark.
Source: OECD Average annual wages, 2025
- H-1B specialty occupation: Employer petition, bachelor's degree or higher in the specialty; annual cap and lottery
- L-1 intracompany transferee: Employees of a related company abroad transferring to a US office
- O-1 extraordinary ability: Evidence of extraordinary ability in sciences, arts, education, business or athletics
Official routes: USCIS
About the role
Full text from the employer, as published on Greenhouse, arranged into sections. Nothing added or removed.
01About 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.
02About 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.
03What 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
04What 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
05Bonus if you
- Built an open source ML tool
- Worked in the trust and safety, fraud, or abuse prevention domain
06Compensation & 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.
07Disclosures
- 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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