About the role
We are looking for a Forward Deployed Machine Learning Engineer with 4+ 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
- High ambiguity tolerance and a strong bias to action in fast-moving environments
- Strong written communication skills for customer-facing and cross-functional work
About Protege
Protege is building the infrastructure layer for AI training data — solving what is arguably the biggest unmet need in AI today: getting access to the right data to train models.
The process of acquiring high-quality training data is time-intensive, incredibly expensive, and often ends in failure. Data holders don't know where to start and are rightly concerned about governance, intellectual property, and security implications. AI companies can spend years finding and negotiating access to the data they need.
Protege solves these problems by providing an easy-to-use platform that connects data holders with vetted data users — facilitating the secure, efficient, and privacy-centric exchange of AI training data.
What makes Protege unique is that they're not just a data broker. The company operates an internal Data Lab that transforms and enriches datasets specifically for AI training, making them significantly more valuable for frontier AI labs and model builders. They partner with organizations across healthcare, media, and other verticals to provide high-quality, real-world training data.
Key highlights:
- $65M in total funding — $55M Series A (August 2025) backed by Andreessen Horowitz, CRV, Bloomberg Beta, Footwork, Shaper Capital, Liquid 2 Ventures, Flex Capital, and a $10M Seed round with investors including Adam D'Angelo and SV Angel.
- Explosive growth — the company hit its entire 2026 goal by June, growing far faster than expected.
- ~80 employees and scaling rapidly with a lean, high-trust team of builders.
- Operating at massive scale — processing up to a trillion images in a single delivery for customers.
Solving AI's data problem is a generational opportunity. The company that succeeds will be one of the largest in AI — and in tech. Protege is positioned to be that company.
Required skills
Other roles at Protege
Refer someone
Know someone great for this role?
Share your link. If they get hired through Standout, you get $3,000.
Job details
Salary
$170,000 - $270,000
Location
Remote
Experience
4+ years
Funding
Total raised
$65M
Last stage
Series A
Investors
Founders
Bobby Samuels
Co-Founder & CEO
What happens next.
No applications, no recruiter spam. Just the intro.
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
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.