Kepler AI

Machine Learning Engineer

New York City

Sponsorship not specifiedDetected 9 days ago

TypeScriptReactPostgreSQLCI/CDMachine LearningdbtNLPLLMsAI OrchestrationResearchLeadershipCollaborationProblem SolvingMentoring

About the role

It means model choice is a permanent engineering problem, and it's yours.
The models you choose and tune sit inside a product financial professionals rely on for million-dollar decisions.
Fine-tune a small model on a high-volume extraction task (footnote tables in 10-Ks, IR decks) and show it beats the frontier model we use today on accuracy, cost, and latency.

Model-agnostic by design doesn't mean the model doesn't matter.
This role is for engineers who want to build foundational technology at the intersection of AI and finance, where your code directly impacts how clients make critical business decisions.
Build an eval harness that scores agent research runs end to end (does every number trace, does every citation resolve) and wire it into CI so regressions get caught before analysts see them.
You'll tell someone their design has a flaw before the PR goes in, not after.
"Build anything" budget - dedicated funding for whatever tools, libraries, datasets, or infrastructure you need to solve technical challenges, no questions asked.
Forward-Deployed with Product DNA: We own customer outcomes while building a product company.
Extreme Ownership: If you notice a problem, you own it by making sure it doesn't fall through the cracks.
Production-First Engineering: We design for critical workloads from day one.
We create an environment where the best idea wins, the strongest work gets recognized, and everyone is held to the same high standard.

You've shipped ML systems to production (fine-tuning, agents, retrieval, structured extraction) and you know what breaks between a demo and a product.
We believe strong engineering fundamentals and experience in other languages is what matters.
You know what it feels like when the plan changes twice in a day and the work still has to ship.

We're backed by investors who built the modern AI and data stacks, plus the builders of iconic commercial businesses.
This includes founders of OpenAI, Meta AI Research, MotherDuck, dbt Labs and Square as well as PebbleBed, Company Ventures and Mantis VC firms.
PostgreSQL, plus direct integrations with official data sources.

Great teams compound.
Every hire raises the bar, every win gets named, every person gets the tools and runway to grow.
Kepler is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.

100% covered top-of-the-line medical, dental, and vision insurance for employees and their families.
HSA maxed by the company to the IRS limit.
Automatic coverage for life, AD&D, and disability insurance.
Unlimited PTO policy.
Learning budget - attend any conference, course, or program that makes you better at what we're building.

The founding team spent a combined 40+ years at Palantir building the type of large-scale data infrastructure that Kepler requires.
Our co-founder created Palantir's first AI platform and built the analytics engine behind $100M+ contracts.
Our founding engineers led Foundry's core systems - Ontology, Fusion, Workshop, FoundryML - and scaled data products at Meta to 1B+ users.
We've paired this deep technical foundation with a repeat founder profile.
Our CEO built and scaled a data company to $15M ARR before successfully selling it.
He then became Citadel's first Head of Business Engineering, experiencing first hand the problems we are now solving.
We have a team who've been on both sides: building systems like this at massive scale and selling it into the buyers who need it most.
We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment.

Equal Opportunity Employer and prohibits discrimination and harassment of any kind.

This listing is sourced directly from Kepler AI's careers page and normalized into a canonical job model.