Forward Deployed Machine Learning Engineer
- Workplace
- Remote
- Compensation
- $170k – $270k + equity
About this role
We are looking for a Forward Deployed Machine Learning Engineer with 3+ years of experience to be the first MLE dedicated to Protege's Benchmarks and Evaluations vertical. You'll work directly with the GM and researchers to build the technical foundation for AI model evaluation — a critical capability at one of the most exciting data infrastructure companies in AI, backed by a16z, CRV, and others.
What will you be doing?
Partner with the GM and early customers to define, design, and build benchmarks and evals across different domains and modalities
Build and own the backend infrastructure: data pipelines, execution environments, storage, and orchestration
Stand up sandboxed environments for agentic evals requiring tools, code execution, or multi-step tasks
Own the engineering portion of customer engagements end to end
Identify repeatable eval patterns and infrastructure gaps to drive product opportunities
Key Requirements
4+ years of engineering experience with hands-on ML model evaluation work
Prior ownership of backend and infrastructure (data pipelines, execution environments)
Experience building benchmarks, evals, or human data pipelines for LLMs (strongly preferred)
High ambiguity tolerance and a strong bias to action in fast-moving environments
Strong written communication skills for customer-facing and cross-functional work
What happens next
Skip the application pile. I get you in front of the people who decide.
Confirm the fit
A few questions to make sure this role is the right shape for you. Two minutes.
I pitch you to the company
I write the intro, send it to the founder, and handle the back-and-forth.
A meeting lands on your calendar
When the company wants to meet, I get the call on your calendar. You just show up.
Know someone who'd be great for this?

