Founding Machine Learning Engineer

The posting, as Arcade wrote it

Everyone's building AI agents, but almost nobody gets them to production.

Building an impressive demo is easy. Building an AI agent that can securely take action inside enterprise systems is hard. The moment an agent accesses customer data, executes a workflow, or makes changes on behalf of a user, authorization, governance, and trust become the real engineering challenge.

Arcade is the MCP runtime that gives agents the power to do both seamlessly. We connect agents to the systems they act in, then give each one a permission slip and a paper trail - proof of what it's allowed to do, and a record of what it did. That's what makes AI safe to turn loose: real actions, on real systems, already shipping inside Fortune 100 companies.

The Revolution Needs You

Every AI app needs agentic "tools" - special functions that let AI models take real actions. Without tools, AI can only chat. With tools, AI can actually do things. We're building the definitive tools catalog and tool-calling platform that will unlock AI's true potential. Think Zapier for AI Actions. Think Auth0 for AI. Think really big.

Why This Is The Opportunity of a Lifetime

• Traction: Real deployments with Fortune 100 Fortune customers.
• Founder-Market Fit: Our CEO was previously the VP of Products for Okta where he led all developer product, all new products, and overall product strategy. Prior to Okta he founded Stormpath (acquired by Okta), where he created the first Authentication API for developers. He's done this before - and this time the market is 10x bigger. Our CTO led the vector database team at Redis, shipped 100+ LLM applications, and is a contributor to LangChain and LlamaIndex. He knows this space better than anyone.
• Dream Team: We've assembled authentication, integrations, distributed systems, and AI experts from Okta, MongoDB, Redis, Microsoft, Meta, Confluent, ServiceNow, Atlassian, Splunk, Ngrok, Google, and Airbyt who've built and founded multiple successful developer platforms.
• Perfect Timing: Every enterprise is racing to put agents in production - almost none get there. The problem isn't better models, it's proving which agent can take which action, on behalf of which user, against which system. That's us.
• Massive Market : We're building critical infrastructure for the biggest technological shift of our generation. Every enterprise agent, whether custom-built on frameworks like LangChain or bought from vendors like Anthropic and Microsoft, needs governed access to the systems it acts in. That's the layer we're building.
• Backed By The Best: Our Series A round is led by SYN Ventures, with strategic investment from Cisco, Morgan Stanley, and Wipro. Our earlier investors have also backed Databricks, Clickhouse, MongoDB, Perplexity, Cohere, ScaleAI, Confluent, Elastic, and Firebase. They see what we see - this is going to be huge.

The Challenge

Arcade is hiring the principal machine learning engineer that wants to build the future
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ht latency budgets, limited GPUs, or someone else's infrastructure (vLLM, ONNX, TensorRT, llama.cpp, or equivalent).

• Strong Python for training and ML work, plus TypeScript or Go for the production services that serve your models.
• You pick the stack, write the doc, and can still defend the decision a year later.
• A do-er, not a researcher-in-residence. You'd rather ship a working v0.5 next week than a polished v2.0 next quarter.
• Comfort with ambiguity: early team, a charter that will expand, decisions made with incomplete data.
• An insatiable desire to ship.

Bonus Points

• You've shipped ML into enterprise on-prem or regulated environments (financial services, healthcare, government).
• Tool-use benchmark or eval work: BFCL, τ-bench, ToolBench, MCP evals, or equivalent.
• Familiarity with the MCP (Model Context Protocol) ecosystem. Extra bonus if you've filed an issue against the spec.
• You've built training-data pipelines from production traces with privacy controls in place.
• You've been the first ML hire somewhere before, and you'd do some things differently this time.
• Open-source contributions or published work that survived contact with other engineers.
• Experience at an early-stage startup, and you loved it.

Join The Movement

We're not just building a product - we're leading a movement to transform AI from just chatbots to agents that can take actions against real systems. This is your chance to be at the forefront of that revolution.

If you want to look back in 5 years and say, "I helped build that", then we want to talk to you. Ready to make AI actually useful? Apply Now

Compensation and Benefits

This role is in person at our San Francisco office, and offers a competitive salary, equity, and benefits. Compensation is aligned with the range below and determined based on a candidate's background, experience, and performance.

Compensation: Starting at $230,000 base salary, plus equity and competitive benefits.