Training Specialist

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 professionals from Fortune 500 pharmaceutical and biotechnology companies (e.g., Pfizer, Merck, J&J, AbbVie, Lilly, Bristol‑Myers Squibb, Roche/Genentech, Novartis, Moderna, Regeneron, Amgen, Gilead, Vertex) and major academic and translational research centers to recreate the digital workspaces they run every day and design the tasks that genuinely challenge state‑of‑the‑art AI. This world combines pharmaceutical clinical development and biotech R&D operations into a single environment — spanning the bench‑to‑clinic lifecycle from discovery and lab research through clinical trials, regulatory submission, and CMC. You’ll bring your expertise across drug discovery, preclinical / translational research, clinical development, bioprocess / lab operations, or regulatory / CMC to build a high‑fidelity environment that mirrors the tools, files, and workflows of a regulated pharma‑biotech enterprise — 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 — study protocols, investigator brochures, IND / NDA / BLA drafts, pharmacology and biomarker analyses, assay and bioprocess development records, CMC technical reports, DMC briefing documents, lab notebooks, and email threads that reflect how you actually organize your work — with some representation of the platforms that support it (e.g., Medidata Rave / Oracle Clinical One, Schrödinger Suite, Benchling / LabArchives) 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 pharma and biotech experts 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 pharma / biotech 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 PhD / MD / PharmD or MS with deep experience; industry fellowship training a plus 3+ years of full‑time experience at a Fortune 500 pharma / biotech or top academic / translational research center Background in one or more areas such as: Target ID / drug discovery (medicinal chemistry, biology, HTS, DMPK) Preclinical / translational research (PK/PD, tox, biomarker) Biotech R&D / bioprocess (molecular & cell biology, assay development, upstream / downstream process development, analytical development) Clinical development (Phase I–IV, biostatistics, clinical operations) Regulatory affairs (IND, NDA, BLA, EMA) or CMC Real‑world evidence / HEOR / pharmacovigilance Day‑to‑day use of Medidata Rave / Oracle Clinical One, Schrödinger Suite / MOE (CCG), and Benchling / LabArchives Strong analytical thinking and writing — able to translate pharma / biotech R&D workflows into structured task specs Compensation Note Task Completion Pay: Competitive and based on task quality (~$1,150 – $1,450 per completed task, subject to change as the project evolves) Performance Bonus: Top performers receive a weekly bonus incentive on top of their per task rate! Hourly Opportunity: Top performers may be invited to transition to an hourly compensation model based on sustained quality and throughput. #J-18808-Ljbffr