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Full-time role at micro1: hands-on ownership of cloud infrastructure reliability, deployments, observability, security and incident response, with AI-agent-driven automation.
Full-time role at micro1: staff-level role designing an automated quality engineering system where AI agents generate tests, run regression suites and triage failures.
Full-time role at micro1: staff-level, hands-on ownership of the data warehouse, ingestion pipelines, transformations and product analytics, building agent-ready data foundations from zero.
Remote contract work (about 15 hours a week, flexible schedule) on an AI training project for Rust backend experts: solve and validate backend problems on APIs, persistence, concurrency, performance and reliability, and prepare reproducible environments and tests.
Remote contract work for simulation experts on an AI training project: build 3D assets and environments in Isaac Sim, Gazebo, MuJoCo or similar, and tune physical parameters so they match real-world behavior. No prior AI experience is required.
Full-time role at micro1: full-stack engineering on internal tools, services and AI-driven workflows, building products from scratch with high ownership.
Full-time role at micro1: design and scale a cross-platform desktop application (macOS and Windows) built with Electron.js.
Full-time role at micro1: build and evolve internal platforms, tools and AI-powered workflows, owning solutions from system design through launch and iteration.
Full-time remote role at micro1: own end-to-end delivery of coding data pipelines used to train frontier AI models, drive automation of task generation, validation, QC and reporting, coordinate experts, reviewers and AI lab clients, and define task specifications, golden samples and review rubrics.
Remote contract work for competitive programmers on an AI training project: solve self-contained coding, logic and debugging challenges designed to test advanced AI models, often in unfamiliar codebases or terminal environments, and produce reproducible solutions.
Remote contract work for machine learning engineers on an AI training project: create, solve and validate ML engineering tasks such as implementing or modifying models, building reproducible training or inference workflows, optimizing memory or throughput and debugging numerical or system failures. The listing describes the role as very coding-heavy.
Remote contract work for application security specialists: build small test applications and deterministic test cases used to evaluate how AI tools and scanners assess application security, write answer keys and documentation, and review peers' contributions. The project focuses on security risks specific to applications that use large language models.
Remote contract work for applied scientists and data scientists: run statistical analyses, build and validate machine learning models, evaluate AI model answers on statistics, machine learning and experimentation problems, and write expert-level prompts, datasets and reference solutions. No prior AI-training experience is required.
You’ll need: clear open source contributions and a profile to showcase them, such as GitHub (preferably with C++, Python, Java, Go, TypeScript, or Rust). If you don’t, you’ll be assessed through a HackerRank assessment instead. Your tasks: Build reproducible Reinforcement Learning Environments that test an AI model’s ability to fix code, add features, refactor, and optimize performance - including a golden reference solution for each problem
You’ll need: clear open source contributions and a profile to showcase them, such as GitHub (preferably with C++, Python, Java, Go, TypeScript, or Rust). If you don’t, you’ll be assessed through a HackerRank assessment instead. Your tasks: Build reproducible Reinforcement Learning Environments that test an AI model’s ability to fix code, add features, refactor, and optimize performance - including a golden reference solution for each problem
micro1 is partnering with a leading AI lab to hire data scientists and quantitative professionals from top companies. You'll bring rigor to how AI models handle statistics, machine learning, experimentation, and quantitative reasoning.
We're looking for data scientists, machine learning practitioners, and applied mathematics experts with competitve Data Science experience. (Kaggle, DrivenData, etc.) You’ll draw on your competition experience, mathematical reasoning, and programming skills to create tasks that require more than a plausible answer. Each task should have a reproducible environment, a verified reference solution, and reliable checks for successful completion.
This is a fullstack software engineering role designed for recent graduates and early-career engineers looking to accelerate their growth by building production systems. You'll contribute to — and grow into owning — core internal platform capabilities and product features end-to-end. You'll work across internal tools, services, workflows, and AI-powered products that support our engineering, operations, and recruiting platforms. As you grow, you'll take increasing ownership of critical systems while collaborating closely with experienced engineers.
Join our team to build and improve a next-generation AI recruiting agent. You'll develop new capabilities, experiment with the latest LLMs and agent frameworks, and ship production-ready AI features that make the agent smarter, more reliable, and more useful.
You'll create realistic, interesting and challenging coding tasks for AI to solve involving feature implementation and bug fixes, and implement deterministic verifiers that accept reasonable valid solutions and reject everything else.