ML Engineer

About Sunset

Sunset is building the data layer for real-world AI training. We work with frontier labs to turn messy, multi-modal enterprise data into the highest-quality training data on the market - sourced from the hundreds of venture-backed startups we help wind down.

We're a fast-growing team based in-person in Dumbo, Brooklyn. Backed by Floodgate, Afore Capital, Hustle Fund, and incredible entrepreneurs.

The Role

As an ML Engineer at Sunset, you'll take the cleaned, resolved data coming out of our pipeline and figure out what to build with it. The raw material is unique - real codebases, tickets, messages, docs, and decisions from real companies, with every linkage preserved. The open question is how to turn that into the most valuable training data on the market. You'll have wide latitude and direct access to the CEO and CTO on direction. All of this happens on deeply sensitive data, so everything we build is designed with security and privacy at the core.

What You'll Work On

You'll own problems end-to-end. Some examples of what you might tackle in your first 90 days:

• Extracting realistic, verifiable agent tasks from linked repos, tickets, and PRs
• Building environments from real company snapshots where the reward signal comes from how work actually got done
• Augmenting datasets with synthetic variants without losing the realism that makes them valuable
• Running experiments to understand which enrichments actually move the needle for the labs buying from us

You Might Be a Fit If

• You've trained or fine-tuned models and shipped applied ML work
• You're creative and high-agency - you'd rather pick the right problem than be handed one
• You're excited about applied work with real data, not academic research
• AI is deeply integrated into your workflow and life

This Role Might Not Be a Fit If

• You want to publish papers as your primary output
• You want to work remote or hybrid - we're in-person 5 days/week in Dumbo
• You want a well-defined roadmap handed to you

Our Stack

Python, Postgres, Redis, AWS. We pick tools based on the problem, not the other way around.

Compensation & Benefits

• $200K-$300K base + meaningful equity
• 100% covered medical, dental, and vision
• Unlimited PTO
• $500 in-office setup allowance

How We Hire

1. Intro Chat (20 min) - mutual fit and interests
2. Technical Session (1hr) - collaborative problem-solving
3. Onsite (2-3 hrs) - product deep dive, system design, meet the team
4. Quick references → Offer