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Sas programmer • chico ca

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Remote Environmental Science Expert - AI Trainer ($50-$70 per hour)

MercorChico, California, US
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Role Overview** Mercor is partnering with leading AI labs on **Project Atlas** — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in.We're ...[internal_linking.show_more]

Remote Public Health Expert - AI Trainer ($45-$65 per hour)

MercorChico, California, US
[filters.remote]
[job_card.full_time]

Role Overview** Mercor is partnering with leading AI labs on **Project Atlas** — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in.We're ...[internal_linking.show_more]

Remote Environmental Science Expert - AI Trainer ($50-$70 per hour)

Remote Environmental Science Expert - AI Trainer ($50-$70 per hour)

MercorChico, California, US
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  • [job_card.full_time]
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  • Role Overview
  • Mercor is partnering with leading AI labs on Project Atlas — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in. We're seeking experienced environmental-science professionals from federal and state agencies (EPA, USGS, state DEPs), major environmental-consulting firms (e.g., AECOM, Jacobs, ERM, Ramboll, Tetra Tech), F500 corporate sustainability teams, and large R1 universities to recreate the digital workspaces they run every day and design the tasks that genuinely challenge state-of-the-art AI. You'll bring your expertise in environmental assessment, compliance, remediation, or sustainability to build a high-fidelity environment that mirrors the tools, files, and workflows of a serious environmental-science practice — and then author tasks grounded in the programs you actually run today. Key Responsibilities - Build a realistic digital workspace centered on the Drive folders you use day-to-day — the site assessment reports, permit applications, monitoring data summaries, environmental impact statements, sustainability / ESG disclosures, remediation workplans, and email threads that reflect how you actually organize your work — with some representation of the platforms that support it (e.g., Esri ArcGIS, SAS or MATLAB, Socrata)

    • Design multi-step tasks grounded in your real workflows that require navigating multiple apps, files, and stakeholders in a way that meaningfully challenges frontier AI agents
    • Collaborate with other environmental-science experts in your field to design the environment, shape task scope, and review each other's scenarios for realism and rigor
    • Work asynchronously with research teams to refine task designs and evaluation criteria for environmental-science agent benchmarks
    • Contribute to frontier AI research and benchmarking — the work you produce directly informs how leading labs train and evaluate the next generation of AI systems Ideal Qualifications - MS / PhD in environmental science, engineering, or related discipline a plus
    • 3+ years of full-time experience at a federal / state environmental agency, major environmental consulting firm, F500 sustainability team, or R1 university
    • Background in one or more areas such as : - Environmental assessment and compliance (NEPA, CWA, CAA, RCRA, CERCLA) - Air, water, or waste permitting and monitoring - Contaminated-site investigation / remediation - Corporate sustainability, ESG reporting, GHG accounting (GHG Protocol, CDP, TCFD, SEC climate rule) - Ecology, natural-resource management, or climate-risk analysis
    • Day-to-day use of Esri ArcGIS / Google Maps Platform, SAS / MATLAB, and Socrata / Esri ArcGIS Hub
    • Strong analytical thinking and writing — able to translate environmental workflows into structured task specs Compensation Note This project is expected to begin on an effective hourly rate, but will transition to a model where experts are compensated based on throughput of quality work rather than a flat accruing hourly rate. About Mercor Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations. Backed by investors including Benchmark, General Catalyst, Adam D'Angelo, and Jack Dorsey. Thousands of professionals across domains contribute to projects shaping the next generation of AI systems.