aimlroles

Applied AI/ML Engineer

Extend extend.app Open · verified Oct 22, 2026
New York Full-time Mid-level Machine Learning Engineering

At a glance

Mid-level Machine Learning Engineering role at Extend. New York · full-time · $200,000–$350,000 base.

SalaryStated by Extend
$200,000 – $350,000
Base salary for this role, in USD per year, as published in the posting.
This role, from ExtendOur estimate for the market: $166,050–$230,000Median $218,200
The range includes the market median of $218,200 for mid-level machine learning engineering roles in New York.
Worked out from 25 postings that stated pay, median $218,200. Last updated Oct 20, 2026.
RoleMachine Learning Engineering
SeniorityMid-level
LocationNew York
EmploymentFull-time
Base pay$200,000–$350,000
PostedDec 15, 2024 · 1y ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build an agent that spots uncertain document results and another that improves processing in the background
  • Develop multimodal models that recognize document layouts and new ways to handle long documents
  • Create data pipelines and measure model performance to guide improvements
  • Watch production models, investigate weak results and test changes to fix them
  • Design LLM methods for more complex document tasks and take ownership of substantial product and engineering work

What you bring

  • You keep current with AI research and can apply it to practical customer problems
  • You approach problems creatively and care about delivering real-world customer impact

Who this fits

This mid-level engineering role suits someone who wants broad ownership and direct customer contact while building applied AI features and document-processing systems. The role is based in person in New York City; relocation support is offered to candidates outside the city.

From the employer

Extend is building a modern document processing platform, reimagined with LLMs. We're on a mission to transform how the world works with unstructured data.

As an AI Engineer at Extend, you’ll be responsible for building state-of-the-art document processing infrastructure and applied AI product features. The work you do will impact every single customer across the millions of documents that our system ingests and processes every month.

We’re looking to hire engineers who think creatively about problems, keep up to date on the latest in AI research, push for real-world customer impact (not only theory), and are excited about helping businesses tackle one of their most painful problems with AI.

Why you should consider joining

  • We've grown revenue 4x last year to several million ARR, with our growth continuing to accelerate

  • We have a product loved by users and being used in mission-critical flows at enterprises (Square, Zillow, Chime) and startups (Brex, Mercury, Checkr), and many more

  • The market for document processing has expanded 1000x due to LLMs, and all existing solutions are low NPS

  • We're punching well above our weight, supporting customer and revenue metrics with half the team size of other startups — everyone joining at this stage will have outsized impact

  • We've raised our series A & de-risked the business, but there's tremendous upside ahead; now's the perfect time to join.

  • You'll be joining a talent dense team (e.g. former founders, world record holders) operating in a high performance culture, in-person in NYC, with high equity ownership

  • We're tackling novel, unsolved problems at the intersection of LLMs, complex data processing, and human ↔ AI interfaces

  • You'll get a front row seat to how a successful startup is built with plenty of leadership opportunities as we grow quickly

We're a lean team, and our customer base is growing too fast for us to keep up. We're looking for talented engineers to join our team and execute on an ambitious roadmap.

Impact

We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).

Here's a few of the complex problems you’ll be working on:

  • Building a QA Agent to flag low confidence results

  • Deploy an optimizer agent in a loop that improves document performance in the background

  • Creating multimodal models for document layout awareness

  • Novel chunking strategies for handling long documents

  • Building data pipelines and evaluating model performance

  • Building a self-correcting system that automatically gets better over time

Role

  • Design novel LLM techniques for increasing the complexity of use cases and data streams that Extend can be applied to

  • Monitor existing models in production, understand what’s working well (and what isn’t), and run experiments to solve those issues

  • Have complete ownership over the work you do — as a founding team member, you’ll have the opportunity to truly own large areas of product and engineering and have direct relationship with customers.

  • Work directly with the CEO, CTO, and other founding members and help build out our team.

Benefits

Beyond the below, we care deeply about each of our candidates on a personal level. We take the time to understand your needs to craft a package designed for you:

  • Insurance - 90% health insurance premium coverage

  • Relocation - for candidates based outside of NYC

  • Unlimited PTO policy - we trust everyone like owners, take what you need

  • Daily lunch & snacks covered (plus dinner if you're in the office late) - you'll never go hungry and you help pick the snacks

  • Unlimited token / tooling access - no handicaps on your productivity

  • Learning and development investment - we invest heavily in our team and support your growth

Extend is an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, citizenship status, marital status, pregnancy, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.