---
title: What it costs to hire an ML engineer through a recruiter
description: A $190k ML engineer costs $38,000 to $47,500 at 20 to 25% contingency. A fixed fee is $15,900 to $21,900 and never rises above that. Worked example inside.
image: https://funded.club/hubfs/og_image_funded.png
---

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# What it costs to hire an ML engineer through a recruiter

![what-it-costs-to-hire-an-ml-engineer-through-a-recruiter](https://funded.club/hs-fs/hubfs/blog-featured-images/fc-cost-to-hire-ml-engineer-recruiter.png?width=1200&height=628&name=fc-cost-to-hire-ml-engineer-recruiter.png)

[Ray Gibson](https://funded.club/blog/author/ray-gibson)

 Sep 30, 2026, 1:53:47 AM

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*Updated September 2026*

Hiring an AI or machine learning engineer through a contingency recruiter usually costs 20 to 25% of first-year base salary, so an illustrative $190,000 hire costs $38,000 to $47,500 in fees. Funded.club charges a fixed fee agreed upfront, which for roles above $150,000 is $15,900 to $21,900 and does not rise further with salary. The higher the salary, the wider that gap becomes.

Machine learning engineers are often among the most expensive people on a startup's hiring plan, which is exactly where a percentage fee hurts most. Before you get to the fee, though, there is a bigger decision. "ML engineer" covers at least three different jobs, and briefing a recruiter for the wrong one is the most costly mistake you can make on this hire.

## Why percentage fees bite hardest on ML hires

A percentage fee is a straight line. Each extra $10,000 of salary adds $2,000 to $2,500 to the recruiter's invoice, with no ceiling. A fixed fee moves in bands and stops at $21,900 per hire, however senior the role.

![Line chart of recruiting fees between $150,000 and $300,000 salary: 20 to 25% contingency rises to $50,000 to $62,500 for a $250,000 hire, while Funded.club's fixed fee stays between $15,900 and $21,900](https://funded.club/hs-fs/hubfs/(01)%20Thumbnails/n04-fee-high-salaries.png?width=1200&name=n04-fee-high-salaries.png)

Take our illustrative applied ML engineer on $190,000. A contingency fee is $38,000 to $47,500, against a fixed fee of $15,900 to $21,900. If competition for the candidate pushes the offer to $250,000, the contingency fee becomes $50,000 to $62,500, and the fixed fee does not change. These salaries are examples to show how the fee behaves, so run the numbers with your own offer range.

That last point matters for ML roles in particular. Strong candidates often weigh several offers, and you may need to raise the package to close. With a fixed fee, improving the offer costs you the salary difference and nothing more.

## Decide which ML engineer you need first

Most early-stage teams need one of three profiles, and they rarely overlap in one person. Research-leaning engineers build and adapt models. Applied engineers put models into the product and measure what users do with them. MLOps or platform engineers make training and serving reliable once there is something to run.

![Diagram of three ML engineering roles: research-leaning ML engineer for when the model is your advantage, applied ML engineer for shipping ML features to customers, and MLOps or ML platform engineer for when models keep breaking in production](https://funded.club/hs-fs/hubfs/(01)%20Thumbnails/n04-ml-role-types.png?width=1200&name=n04-ml-role-types.png)

If you are building features on top of existing foundation models, you almost certainly want an applied engineer first. Hiring a research profile for that work often leads to long experiments and a frustrated hire. If your advantage is a model nobody else has, the order flips, and the applied and platform hires come after.

## How to brief a recruiter on an ML role

- **Describe the problem, not the stack.** "Rank 2 million products for each user in under 100 milliseconds" tells a recruiter far more than a list of frameworks.
- **Say what exists today.** Is there training data, a baseline model, a pipeline? Candidates will ask, and the answer decides which profile fits.
- **Agree how you will assess depth.** If nobody on the team can judge ML work, line up an advisor or a paid take-home review before the first interview.
- **Set the offer range before you start.** Know how far you can stretch on cash and equity, so you can move quickly when a strong candidate appears.
- **Price the search at the top of the range.** With a percentage fee, budget for the offer you might end up making. With a fixed fee, check which band applies on the [pricing page](https://funded.club/pricing).

## Where Funded.club fits

We're a fixed-fee recruiting partner for funded startups and fast-growing teams across North America, Europe and APAC. Since 2019 we've helped 500+ startups from Seed to Series D build engineering, product and go-to-market teams, including senior technical hires.

Our fee is agreed before the search starts, averages 6 to 9% of salary and runs from $4,900 to $21,900 per hire. Part of it is an advance at the start of the search, and the balance is due when your candidate accepts the offer. If we don't deliver a shortlist of at least 3 qualified candidates within 30 days, you can claim the advance back in full. First-time customers can ask to defer the advance until they see their first candidates.

One dedicated recruiter runs your search end to end, from sourcing and headhunting through screening and offer support. You'll see first screened candidates within 7 days, and the average time from kick-off to hire is 33 days. For more on the fee models themselves, read [how much a recruiter costs for startups](https://funded.club/blog/how-much-does-a-recruiter-cost-for-startups).

## Frequently asked questions

### How much does a recruiter charge to hire a machine learning engineer?

Contingency recruiters typically charge 20 to 25% of first-year base salary, so an illustrative $190,000 ML engineer costs $38,000 to $47,500 in fees. Funded.club's fixed fee for roles above $150,000 is $15,900 to $21,900.

### Is there a cap on Funded.club's fee for high-salary AI roles?

Yes. Funded.club's fees run from $4,900 to $21,900 per hire, so even a very senior AI or ML role is priced within that range and agreed upfront.

### What is the difference between an applied ML engineer and an ML researcher?

An applied ML engineer puts models into your product and measures their impact on users. A research-leaning engineer builds or adapts the models themselves. Most startups building on existing models need applied engineers first.

### How do I assess an ML engineer if I'm not technical?

Bring in someone who can judge the work, such as an advisor or experienced engineer, and use a short, paid exercise based on a real problem. A recruiter can screen for experience, but a technical review is still worth doing before an offer.

Worth a brief chat about your next hire? [Book a free call](https://funded.club/contact-us).

## Hiring after a funding round?

 First candidates in 7 days. Fixed-fee, no commission.

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```