We’re building the first end-to-end evaluation and training platform for web agents. Our system enables teams to test, benchmark, and optimize browser automation models at scale.

• Deterministic Web Simulation → Stable, reproducible testing with versioned web snapshots.
• Live Web Evaluation → Identify failures caused by UI drift, captchas, and dynamic content.
• Automated Annotation & Labeling → Generate high-quality training data for benchmarking.
• RL-Driven Agent Optimization → Improve models with scalable, feedback-driven learning.

By combining synthetic user simulations, automated evaluations, and large-scale benchmarking, we help teams build more reliable web agents that handle real-world environments with confidence.

Location: San Francisco, CA

Why Foundry Exists: Most of what people do at work sucks—it's manual, repetitive, and wastes time. Recruiters spend hours every day on LinkedIn, CRMs, email, and tedious data entry tasks instead of focusing on the things humans actually do well: building relationships, strategy, and decision-making.

We're building tools so that AI agents can use web browsers exactly like humans, navigating enterprise apps like Salesforce, SAP, or Workday without constant manual intervention. Enterprises like Accenture staff entire teams and charge premium rates just to manage complex platforms like Salesforce, because navigating and operating these systems is so challenging. Right now, browser agents—even those built on GPT-o3—fail most of the time, get stuck on basic UI changes, and require endless manual debugging. This isn't sustainable.

Foundry creates the infrastructure to fix this: precise simulations, robust evaluation tools, and direct support for AI labs trying to get these browser agents to actually work in the real world. We're applying the same proven playbook used by Waymo for autonomous vehicles and Scale AI for large language models—developing rigorous, reliable infrastructure to rapidly improve agent performance.

Big players like OpenAI (Operator), Anthropic, and Mariner are investing heavily here, and it's clear why: McKinsey estimates around 60% of jobs have tasks that are automatable, representing over $15.8 trillion globally. We're at the front of this wave, creating essential tools that make AI-powered automation realistic and reliable.

Who We’re Looking For: You're an elite engineer. You're impatient with bureaucracy and thrive when shipping real, foundational technology quickly.

What You’ll Actually Do:

• Build and refine infrastructure for next-gen AI digital workers.
• Collaborate directly with top ML researchers and product leaders.
• Solve tough engineering challenges around browser automation, distributed systems, and ML in production.

You Probably:

• Have landed internships or jobs at reputable tech companies or built impressive projects—whether it's sneaker bots, unique web apps, or standout open-source contributions. Exceptional coding skills, strong LeetCode rankings, or competitive programming achievements are a plus.
• Have impressive projects, internships, side projects, or notable OSS contributions.
• Ship fast, iterate quickly, and respond well to real-world feedback.

Bonus Points If You:

• Have experience with React/Next (Typescript), FastAPI (Python), Web Sockets, Postgres, Redis, Pub/Sub, Message Queues (e.g. RabbitMQ), Playwright, Docker, Kubernetes, Github CI/CD
• Are bored by incremental ML work and want deeper challenges.
• Have hands-on ML experience: training models, building infrastructure, running experiments.

Why Join Foundry:

We want to build a team around you—giving you the space, resources, and support you need to lead and grow.

We are a tight-knit team of former Scale AI operators and ML researchers who have firsthand experience scaling groundbreaking AI technologies.

• Do foundational ML work that actually matters.
• Join an experienced founding team from Meta and Scale AI.
• Competitive pay, solid equity, real career growth.

If you're excited about actually building something important—reach out. We'd love to talk to you.