Posted
19 Aug 2026
Last seen
19 Aug 2026
Location
Remote
Lifecycle
fresh
Grade
C
Role Title: STEM AI Agent Research SpecialistRole Type: ContractorLocation: Remotemicro1 is engaging STEM AI Agent Research Specialists to contribute to a customer's advanced AI training project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This engagement focuses on reviewing and analyzing historical session traces from local or agentic AI tools used in rigorous STEM research or technical problem-solving. Strong written and verbal communication skills are essential, as you will assess, document, and articulate technical processes and insights for project deliverables.Scope of Work
Review, curate, and submit historical session traces from local or agentic AI tools (e.g., Claude Code, Claude Cowork, Codex, Claude for Life Sciences, OpenCode) demonstrating substantive STEM research or technical workflows.
Analyze and validate the technical depth and integrity of AI-assisted problem-solving, ensuring sessions involve multi-step reasoning and authentic human guidance.
Document research methodologies, problem-solving approaches, and points of human intervention within session traces.
Evaluate the effectiveness and limitations of agentic AI tools in STEM research contexts, highlighting areas for improvement or model training.
Produce clear, concise written explanations outlining session processes, outputs, and validation steps.
Provide constructive feedback on the AI’s performance, accuracy, and reasoning based on professional STEM experience.
Preferred Qualifications
Advanced academic or professional background in a STEM field (science, technology, engineering, or mathematics).
First-hand experience using local or agentic AI tools for research or technical projects, beyond web-based chatbots.
Access to and familiarity with historical session data involving STEM or technical workflows.
Strong skills in scientific reasoning, technical research, data analysis, code debugging, and research documentation.
Demonstrated ability to guide, challenge, and validate AI-generated outputs within complex problem-solving scenarios.
Excellent written and verbal communication skills for clear technical documentation and feedback.
Experience with AI evaluation, output validation, and iterative research methods is highly valued.
Originally posted on Himalayas
Review, curate, and submit historical session traces from local or agentic AI tools (e.g., Claude Code, Claude Cowork, Codex, Claude for Life Sciences, OpenCode) demonstrating substantive STEM research or technical workflows.
Analyze and validate the technical depth and integrity of AI-assisted problem-solving, ensuring sessions involve multi-step reasoning and authentic human guidance.
Document research methodologies, problem-solving approaches, and points of human intervention within session traces.
Evaluate the effectiveness and limitations of agentic AI tools in STEM research contexts, highlighting areas for improvement or model training.
Produce clear, concise written explanations outlining session processes, outputs, and validation steps.
Provide constructive feedback on the AI’s performance, accuracy, and reasoning based on professional STEM experience.
Preferred Qualifications
Advanced academic or professional background in a STEM field (science, technology, engineering, or mathematics).
First-hand experience using local or agentic AI tools for research or technical projects, beyond web-based chatbots.
Access to and familiarity with historical session data involving STEM or technical workflows.
Strong skills in scientific reasoning, technical research, data analysis, code debugging, and research documentation.
Demonstrated ability to guide, challenge, and validate AI-generated outputs within complex problem-solving scenarios.
Excellent written and verbal communication skills for clear technical documentation and feedback.
Experience with AI evaluation, output validation, and iterative research methods is highly valued.
Originally posted on Himalayas