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AI Research Scientist

GenMD

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Seed raised
840k - 1440kFULL TIMERemote · Asia-Pacific13 employeesPosted Oct 6
large language modelspytorchhugging facesynthetic data generationmodel evaluationpythonmachine learningnatural language processingmodel trainingfine-tuningsupervised learningunsupervised learningmixture-of-expertsmodel distillation

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Silicon Valley Startup | Collaboration with Stanford Researchers

GenMD is a Stanford spin-off building AI and data infrastructure for healthcare. We are looking for an AI Research Scientist to work on large language models (LLMs), synthetic data generation, model evaluation, and scalable model training.

The company was built out of years inside Stanford Medicine, working closely with world-class researchers and clinicians. We have access to tens of millions of patients, longitudinal health records, and clinical notes. GenMD is just coming out of stealth, already revenue-generating, well-funded, and backed by premier investors with years of runway. We’re intentionally small, move fast, and are focused on building something fundamental. CEO is a former Associate Director of AI, Stanford Medicine, Stanford University.

What You'll Work On

  • Train, fine-tune, and optimize LLMs using PyTorch and Hugging Face.

  • Build synthetic data generation pipelines at scale.

  • Develop LLM benchmarks, automated evaluation pipelines, and LLM-as-a-Judge systems.

  • Experiment with supervised, semi-supervised, and unsupervised learning.

  • Explore Mixture-of-Experts (MoE), model ensembles, distillation, and other modern LLM techniques.

  • Translate research ideas into reproducible experiments and production systems.

Preferred Candidate

  • Strong hands-on expertise working with LLMs.

  • B.Sc. (minimum) in CS, AI, ML, NLP, or a related field; thesis work in LLM/NLP strongly preferred.

  • Publications in LLM/NLP are strongly preferred.

  • Strong Python skills with experience in PyTorch, Hugging Face, model training, fine-tuning, and evaluation.

What We Offer

  • Fully remote work.

  • Approximately 50% working-hour overlap with California office hours, typically 9 AM-1 PM Pacific Time.

  • Access to high-performance GPU servers, including A100 GPUs, for model training and fine-tuning.

  • Opportunity to collaborate with Stanford researchers.

  • Opportunities to develop benchmarks and publish research papers in conferences and journals.

  • Work directly on challenging, real-world LLM and healthcare AI problems.

  • Salary: BDT 70,000-120,000/month (based on experience and expertise).

  • Full-time employment (40 hours/week).

  • Start date: As soon as possible.

     

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