Job Category: Coding & Engineering

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 part-time contract work (about 10–20 hours per week) for a research project with a leading AI lab: on your own Mac, carry out and narrate real software development workflows so the work can be used to benchmark and improve AI models. The work is done on your own computer: read the privacy terms on the official page before applying.

Remote part-time contract work (about 10–20 hours per week) for a research project with a leading AI lab: on your own Mac, carry out and narrate real data analysis workflows so the work can be used to benchmark and improve AI models. The work is done on your own computer: read the privacy terms on the official page before applying.

Remote part-time contract work (about 10–20 hours per week) for a research project with a leading AI lab: on your own Mac, carry out and narrate real productivity and automation workflows so the work can be used to benchmark and improve AI models. The work is done on your own computer: read the privacy terms on the official page before applying.

We are seeking highly qualified Domain Experts (SMEs) to support the evaluation, testing, and improvement of advanced Large Language Models (LLMs). You will apply your subject-matter expertise to assess AI-generated responses, identify knowledge gaps, design challenging prompts, and improve model accuracy, reliability, and reasoning. Main tasks listed: Create complex, domain-specific prompts to test LLM capabilities; Evaluate AI-generated responses for factual accuracy, reasoning, relevance, and overall quality; Identify factual errors, logical inconsistencies, knowledge gaps, and model weaknesses; Develop challenging test cases and edge cases that expose model limitations.

We are hiring US-based academic dermatologists to contribute senior clinical expertise to data curation for frontier AI models and labs. The work supports a longitudinal dermatology dataset used by AI developers, regulatory teams, and academic groups. This is the senior reviewer track of the project. You will lead clinical review on complex cases, contribute to the development of clinical evaluation frameworks, and serve as expert advisor for client teams reviewing AI model outputs. Main tasks listed: Lead senior-level clinical review on complex or ambiguous cases; Facilitate structured resolution of clinical disagreement among reviewers; Contribute to the development of clinical evaluation frameworks; Provide expert advisory hours to client teams reviewing AI model outputs. The listing says the work can involve sensitive or graphic content.

This role is part of a project supporting leading LLM companies. The primary objective is to help these foundational LLM companies improve their Large Language Models. We support companies in enhancing their models by offering high-quality proprietary data. This data can be used as a basis for fine-tuning models or as an evaluation set to benchmark the performance. Main tasks listed: Translate CUDA/C++ code into equivalent Python implementations using PyTorch and NumPy, ensuring logical and performance parity; Analyze CUDA kernels and GPU-accelerated code for structure, efficiency, and function before translation; Evaluate LLM-generated translations of CUDA/C++ code to Python, providing technical feedback and corrections; Collaborate with prompt engineers and researchers to develop test prompts that reflect real-world CUDA/PyTorch tasks.

We are looking for Software Engineers to work with a leading Frontier LLM Lab to help accelerate their Agentic Data Cloud roadmap by building and scaling tools for next-generation AI-powered data systems. You will work on developing MCP tools, improving AI-assisted developer workflows, and expanding platform capabilities across the Data Cloud ecosystem. Main tasks listed: Build and enhance MCP tools for both proprietary and open-source environments; Expand test coverage for tools used by AI coding assistants (e.g., Gemini CLI, Claude Code); Refactor, maintain, and improve existing test frameworks and codebases; Convert technical blogs into production-ready sample code and documentation.

We are looking for experienced Software Engineers with a strong background in developing and operating large-scale production systems. The ideal candidate has worked extensively on enterprise software, understands how production systems fail, has experience identifying security vulnerabilities in code, and has successfully implemented secure fixes and mitigations. Main tasks listed: Design and build realistic coding-agent benchmark tasks using production-like repositories, tests, configs, documentation, and runtime scenarios; Create benign engineering tasks such as bug fixes, feature additions, CI repairs, config migrations, integration updates, and runtime-state fixes; Define clear utility requirements to verify that the coding agent completes the requested task correctly; Define safety/alignment requirements to ensure the agent preserves system constraints, developer intent, data integrity, privacy, permissions, and oversight mechanisms.