Machine Learning Engineer, Trust & Safety
At a glance
Mid-level Machine Learning Engineering role at Vercel. San Francisco · $208,000–$312,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and run dependable, observable systems that identify and interrupt abusive activity across the platform
- Create ML foundations for training, feature generation, model serving and evaluation
- Turn LLM and conventional ML prototypes into maintainable abuse-detection and classification systems
- Take models from platform integration through release, monitoring and continued improvement
- Translate abuse patterns into deployed detection systems with security, product and infrastructure teams
What you bring
- At least five years building and operating production software systems at scale
- Production Python experience, plus hands-on work in JavaScript, TypeScript or Go
- Experience developing and maintaining ML infrastructure, including pipelines, feature stores or evaluation tools
- You have deployed LLMs in production, with prompt design and evaluation experience
Who this fits
This suits an engineering-focused machine learning role, with most of the work devoted to shipping production code and some time spent on modeling. You’ll work from a San Francisco or New York City office three days each week.
From the employer
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.