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3d ago
Natera United States $146k - $183k/yr
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Why this grade This listing scored 34/100, which is an F. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
-10 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Role Title: Data-heavy chemistry/materials Science Expert
Role Type: Contractor
Location: Remote
micro1 is engaging Data-heavy chemistry/materials Science Experts to contribute to a cutting-edge customer project centered on leveraging AI agents for scientific advancement. 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 opportunity is ideal for professionals who have integrated advanced AI coding agents, such as Codex, Claude Science, Claude Code, and Claude Cowork, into their technical workflows for complex chemistry or materials science initiatives. Contributors should be adept at written and verbal communication and able to articulate their problem-solving strategies, technical challenges, and how AI agents were leveraged to generate code sequences — not simply as chat interfaces.
Scope of Work
- Deliver comprehensive, data-rich insights based on your experience in chemistry or materials science, especially where AI coding agents have been integral to your process.
- Document real-world scenarios where you utilized AI agents for tasks such as large codebase navigation, challenging debugging, feature development, or architectural modifications.
- Compose clear, detailed written accounts and participate in feedback sessions to elucidate your methodologies and the impact of AI tools on scientific problem-solving.
- Evaluate the effectiveness and limitations of AI agents in technical workflows, providing actionable recommendations for improving AI systems in STEM contexts.
- Collaborate remotely with micro1’s project team, sharing domain-specific expertise and facilitating knowledge transfer through written and verbal channels.
- Contribute to the development of datasets and training materials that reflect authentic chemistry/materials science practice using AI code-generation tools.
- Identify unique case studies or complex technical challenges where AI coding agents enhanced productivity or enabled new scientific outcomes.
Preferred Qualifications
- Advanced degree (or equivalent professional experience) in chemistry, materials science, chemical engineering, or a closely related STEM field.
- Proven proficiency with AI coding agents, including Codex, Claude Science, Claude Code, and Claude Cowork, specifically for generating code sequences in scientific environments.
- Demonstrated ability to apply AI agents beyond code assistance — such as debugging intricate issues, building end-to-end features, and addressing ambiguous scientific problems.
- Track record of contributing to projects involving large or complex codebases in computational chemistry, materials modeling, or laboratory automation.
- Exceptional written and verbal communication skills, with a focus on clarity in technical documentation and knowledge sharing.
- Experience in evaluating, adopting, or pioneering new workflows or methodologies using AI-powered tools within scientific research or industrial settings.
- Strong analytical and critical-thinking capabilities, with the ability to articulate process decisions and results effectively for AI system training purposes.
Originally posted on Himalayas
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Where this listing came from
- 20 Aug 2026 Himalayas first sighting
Seen on 1 board over 0 days.