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Founding Algorithm Developer

Open 62d

Fleetline writes optimization algorithms for enterprise trucking fleets. We work with some of the largest fleets in the country and are rapidly scaling our operations.

A bit about us

  • Scaled from 0 to $Xm in contracts in under eight months; month-over-month growth is still increasing

  • Lean team of 12 based in New York City; everyone deeply cares about the company’s mission, our clients, and each other. That care translates into high standards, close relationships, and intensity.

  • Backed by a large seed round from top investors like BoxGroup, Base10, and more.

About the role

  • Build and scale core optimization algorithms used directly in production

  • Write optimization systems (e.g. MILPs, LPs, heuristics, etc.)

  • Build and maintain data pipelines that operate at real production scale

  • Move quickly from idea → implementation → customer usage

  • Contribute to long-term product and technical direction

  • Willingness to do whatever is needed technically, from deep algorithm work to integration and tooling

  • Comfortable being forward-deployed: talking to customers, understanding constraints, and solving concrete problems

  • In office in New York City is required.

What we’re looking for

  • Has experience writing optimization algorithms (MILPs, ML, DP, RL, stochastic models, heuristics, or similar)

  • A generalist who can operate across the stack when needed

  • Ships code fast and often; not a perfectionist

  • Comfortable working in ambiguity with incomplete information

  • Extremely hardworking when part of a strong, mission-aligned team

  • Background may include top startups or big tech, ex-founder / founding engineer experience, or serious side projects that are shipped and live

  • Comfortable with Python and TypeScript

Pedigree is not important. We’re looking for people who are intelligent, gritty, curious, and good at moving quickly.

What this application asks

ashby

Name, Email, Resume

  • Phone Number
  • Github
  • LinkedIn

See also

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