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About This Role
Marketing
United States
Full Time
About Vercel:
Vercel is the agentic infrastructure company. We free people and agents to ship what’s next.
For more than a decade, Vercel has shaped how the web is built. As the team behind Next.js, v0, and AI SDK, we create products that help builders move from idea to production with speed, security, and exceptional developer experience.
Now, software is entering a new era, and the next generation of products will not just be used by people. They will be built, extended, and operated by agents.
We are building the platform for that future, trusted by companies like OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. Whether you’re building our products, supporting our customers, growing our community, or shaping our story, you’ll help define what comes next.
About the Role:
Vercel is seeking an AI Accelerator Lead to own the Vercel AI Accelerator end to end and help make it the best program for pre\-seed and idea\-stage founders building the next generation of AI applications.
The Vercel AI Accelerator gives us early access to promising AI\-native founders before they have made long\-term infrastructure decisions, built their full stack, raised institutional capital, or locked in their go\-to\-market motion. This role will own the full program lifecycle across strategy, applications, selection, cohort experience, programming, founder engagement, community, partner credits, Builder Day, Demo Day, content, and post\-program follow\-up.
You’ll work closely with our Startups, Community, Content, Media, Product Marketing, Developer Relations, Partnerships, and Events teams to create a world\-class founder experience that helps technical founders move from idea to product, and product to company.
This role is ideal for an operator who understands early\-stage startups, is excited by AI\-native company creation, can manage complex cross\-functional programs, and knows how to create community, content, and founder trust at the same time.
What You Will Do:
Own the Vercel AI Accelerator strategy, roadmap, operating model, and execution end to end, with the goal of running multiple high\-quality cohorts per year.
Design and run a repeatable program for pre\-seed and idea\-stage AI founders, helping them move from early idea to working product, clearer company narrative, and stronger technical foundation on Vercel.
Own the full cohort lifecycle, including applications, selection, founder onboarding, programming, community engagement, partner credits, Demo Day, post\-program follow\-up and content.
Build scalable systems for application review, founder communications, partner activation, content production, and cohort operations.
Partner with Startups, Community, Content, Product Marketing, Vercel Media, Developer Relations, Product, and Engineering to create a world\-class founder experience and surface strong founder stories.
Build trusted relationships with founders, VCs, accelerators, operators, and AI ecosystem partners, and bring founder insights back into Vercel’s product, marketing, community, and startup strategies.
About You:
5\+ years of experience in startup programs, accelerators, ecosystem, community, partnerships, founder relations, venture, or strategic programs, ideally in a high\-growth technology or developer\-focused company.
Experience owning complex programs end to end, from strategy through execution, measurement, and iteration.
Deep understanding of early\-stage founders, especially pre\-seed, idea\-stage, or technical founders building from 0 to 1\.
Strong interest in AI\-native startups, developer tools, infrastructure, and the changing ways founders are building products with AI.
Proven ability to build high\-quality founder or community experiences that combine programming, relationships, content, and operational excellence.
Strong cross\-functional operator who can work effectively across Startups, Community, Content, Media, Product Marketing, Developer Relations, Product, Engineering, Partnerships, Events, Legal, and Sales.
Strong editorial and storytelling instincts, with the ability to identify compelling founder stories and turn them into useful internal or external content.
Clear, concise communicator who is comfortable engaging technical founders, managing ambiguity, and building repeatable systems for scale.
Bonus If You:
Have built or run an accelerator, fellowship, founder community, demo day, or venture\-backed startup program.
Have worked directly with pre\-seed or idea\-stage founders, AI startups, OSS developers, or technical founder communities.
Have experience creating content programs, founder spotlights, cohort announcements, or media moments around startup communities.
Have worked with developer\-first products or are familiar with modern web and AI tooling such as Vercel, Next.js, v0, AI SDK, AI Gateway, Cursor, Claude Code, or similar tools.
Have hosted or produced founder\-facing events, workshops, demo days, or community gatherings.
Have been a founder, early startup employee, investor, operator, or community builder yourself.
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 $114,000 \- $172,000\. 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.
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.
Salary Context
This $114K-$172K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Vercel, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($143K) sits 35% below the category median. Disclosed range: $114K to $172K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Vercel AI Hiring
Vercel has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in US. Compensation range: $172K - $172K.
Location Context
AI roles in Austin pay a median of $214,343 across 87 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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