Platform Engineer

Prediction Lab

Northern (KY)

Hybrid

USD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Remote-first culture
Competitive equity
Full remote flexibility

Job summary

Prediction Lab is a remote-first B2B SaaS startup focused on predictive modeling. We build a platform for teams and agents, leveraging ML and AI advancements to deliver fast, reliable modeling capabilities.

As a Platform Engineer, you will own the application infrastructure from deployment to monitoring, collaborating with the founder and users to shape a product that users love. You’ll drive security, reliability, and performance at scale.

Qualifications

  • Experience building and operating production infrastructure at a software company with a high engineering bar.
  • Strong programming skills across backend services and cloud infrastructure.
  • Track record of taking complex systems to production and keeping them reliable under load.
  • Experience owning incident response, from paging through postmortem.
  • Cares deeply about security, observability, and operational maturity.

Responsibilities

  • Build and operate the infrastructure our platform runs on, from design to production.
  • Lead infrastructure innovation focusing on performance and cost at scale.
  • Own security, reliability, and disaster recovery for data and models.
  • Shape the product and its future with input from users and the founder.
  • Elevate the team by sharing ideas and expertise.

Skills

Production infra
Backend services
Cloud infrastructure
Security
Observability
Autonomy
Remote work
Predictive modeling knowledge

Tools

Rust
PostgreSQL
AWS
TypeScript
React
GraphQL
Codex/Claude Code

Job description

At Prediction Lab, we're building the predictive modeling platform for teams and agents. AI has fundamentally changed how software gets built, and we're bringing that same transformation to predictive modeling.

Founded in 2025, Prediction Lab is a B2B SaaS company looking to hire a world-class team of builders to lead the way in predictive modeling. We're passionate about enabling our users to solve real-world problems with the latest advancements in machine learning and generative AI. We focus relentlessly on delivering the best value to our users, ship with incredible speed, and care deeply about the user experience.

As a small team, we're all generalists that work across the full stack and have deep expertise in predictive modeling. We're looking for builders that thrive in an environment of autonomy, ownership, and individual responsibility to help us create the future for predictive modeling.

Location & work mode

Prediction Lab is a remote-first company that values deep focus and asynchronous collaboration, with intentional moments to connect in person through team off-sites and occasional travel.

About the role

We're seeking a Platform Engineer who is passionate about building a product that our users love. You'll work closely with the founder and users to design and implement new concepts and ideas.

You’ll own the application infrastructure, from deployment to monitoring, and be responsible for delivering the best value to our users. Your decisions will shape the product and its future.

What you’ll do
  • Build and operate the infrastructure our platform runs on, owning it from design to production
  • Lead infrastructure innovation, with a focus on the performance and cost of running training and inference at scale
  • Own security, reliability, and disaster recovery, so our users’ data and models stay safe and available
  • Shape the product and its future, to lead the new era of predictive modeling
  • Elevate the team, by bringing your own ideas and expertise to the table
  • Partner with the founder, to build a product that our users love
What we’re looking for
  • Experience building and operating production infrastructure at a software company with a high engineering bar
  • Strong programming skills, with experience across backend services and cloud infrastructure
  • Track record of taking complex systems to production and keeping them reliable under load
  • Experience owning incident response, from paging through postmortem
  • Cares deeply about security, observability, and operational maturity
  • Comfortable working in a fast‑paced, startup environment
  • High level of autonomy and ownership
  • Thrives in a remote, asynchronous environment with a lean, high-output team
  • Domain knowledge in predictive modeling and data science
You’ll love this if

You want to build infrastructure that the whole team can depend on. You are passionate about predictive modeling and hold high opinions about how systems should be built and run. You want to work with a world‑class team that values your input and your ideas.

You’ll hate this if

We work a lot and we work hard. We think through problems from first principles and are comfortable with ambiguity. We are not afraid to take the lead on complex problems & shape the solution, not just follow instructions.

Our tech
  • Rust, Postgres, AWS on the backend
  • Typescript and React on the frontend
  • GraphQL API, with SDKs in several languages
  • Claude Code / Codex
  • Github, Linear, Slack
What we offer

We're a small, focused team that cares deeply about the quality of our work and the people we do it with. Here's what you can expect:

  • Competitive salary and equity
  • Full remote flexibility and asynchronous work culture
  • 100% employer-paid health insurance, including dental and vision coverage
  • Unlimited paid time off
  • A high degree of ownership, autonomy, and the opportunity to help build a growing company
  • The ability to make a meaningful impact while working alongside a passionate, high-performing team
  • Exposure to the challenges and opportunities of a fast‑paced startup environment

Prediction Lab is an equal opportunity employer. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.

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