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Machine Learning Researcher - Agentic Science

9 hours, 7 minutes ago
Anywhere
Full-time
Senior
AI Research Scientist
Data Science and Analytics
Deep Learning Machine Learning Python PyTorch
Apply Now
PostEra

PostEra

PostEra is a cutting-edge biopharma using machine learning to speed up drug discovery and cure development, with major funding and partnerships in place.

Industrial Conglomerates
11-50
Founded 2019
$94M raised
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Description

  • Develop and benchmark agentic systems for quantitative biological and physiological modeling and biological-data analysis.
  • Independently define and lead research projects in in-context learning, agentic systems, few-shot adaptation, tabular foundation models, and molecular machine learning.
  • Design and train models that adapt to new assays, endpoints, targets, and chemical series from limited labeled data.
  • Define research tasks, construct datasets and evaluation episodes, build baselines, and conduct rigorous ablations.
  • Develop efficient training and data pipelines and scale models across molecular and tabular tasks.
  • Collaborate with chemists, biologists, and other scientists to connect modeling objectives to drug discovery decisions.
  • Produce reproducible research code, maintain tracked experiments, and contribute to shared modeling infrastructure.
  • Publish research in machine learning, medicinal chemistry, or computational biology venues and represent PostEra in the scientific community.

Requirements

  • PhD in machine learning or a STEM field involving novel machine learning research.
  • Track record of high-quality research through publications, open-source contributions, or similar work.
  • Strong research or engineering experience in modern machine learning, deep learning, or statistical modeling, including underlying theory.
  • Expertise in at least one of agentic workflows for science, bioinformatics or clinical-data modeling, in-context learning, tabular learning, or few-shot learning.
  • Hands-on experience training, debugging, and evaluating ML models in Python with PyTorch, JAX, or similar frameworks.
  • Ability to turn ambiguous scientific or technical problems into well-defined ML projects with datasets, baselines, metrics, and validation schemes.
  • Ability to design experiments, benchmarks, and ablations that distinguish genuine improvements from bias.
  • Comfort working in a startup environment with evolving priorities and imperfect data.
  • Experience training tabular foundation models for sparse, heterogeneous, small-data, or high-missingness settings (preferred).
  • Experience with molecular in-context learning, large-scale distributed model training, AI co-scientist systems, biological or clinical ML, or production scientific software (preferred).

Benefits

  • Salary of $200,000–$300,000.
  • Equity grant of 0.05%–0.1%.
  • Meaningful promotion and internal recognition opportunities.
  • Opportunity to publish research and contribute to scientific communities.

Interested in this position?

Apply directly on the company website

Apply Now

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