Machine Learning Researcher - Agentic Science

PostEra· Machine Learning

Remote$200k - $300k + equityFull-timePosted 2w ago

About the role

Role focused on developing agentic research verticals to automate mechanistic modeling for biochemical and physiological processes, analyzing biological data for target validation, and advancing ML methods for drug discovery with emphasis on in-context learning and foundation models from proprietary multimodal data.

Responsibilities

Agentic Research for Chemistry and Biology: Develop and benchmark agentic systems to automate the development of quantitative models to simulate biological and physiological processes, and the analysis of biological data.
Research Direction and Execution: Independently identify, formulate, and lead research projects involving in-context learning, agentic systems, few-shot adaptation, tabular foundation models, and molecular machine learning.
In-Context Learning for Molecules: Design and train models that adapt to new assays, endpoints, targets, or chemical series using limited labeled context and heterogeneous historical data.
Benchmarking: Rigorously compare new approaches against strong baselines, curating test cases that deconfounds impact of different sources of bias.
Cross-Functional Collaboration: Work with scientists to connect modeling objectives and evaluation metrics to practical decisions in potency modeling, ADME prediction, selectivity, lead optimization, and early clinical studies design.
Model Training and Scaling: Develop efficient training and data pipelines and, where appropriate, scale models across large collections of molecular and tabular tasks.
Research Engineering: Produce readable, reproducible research code; maintain well-tracked experiments; contribute through code review, documentation, and shared modeling infrastructure.
Scientific Dissemination: Publish results in leading ML, medicinal chemistry, or computational biology venues and represent PostEra in the scientific community.

Qualifications

PhD degree in machine learning, or STEM research involving the development of novel machine learning approaches
Track record of high-quality research, such as publications and open-source contributions
Strong research or engineering experience in modern machine learning, deep learning, or statistical modeling, with understanding of ML theory
Expertise in at least one area: agentic workflows for science, ML approaches to bioinformatics and clinical data modeling, in-context learning, tabular learning, few-shot learning
Hands-on experience training, debugging, and evaluating ML models in Python using PyTorch or JAX
Ability to independently translate ambiguous scientific or technical problems into well-defined ML projects (datasets, tasks, baselines, metrics, validation)
Ability to design careful experiments, benchmarks, and ablations that distinguish improvements from biases
Comfort working in a startup where priorities evolve and data is imperfect

Skills

Required:Agentic systems for sciencein-context learningFew-shot learningMolecular machine learningPython (PyTorch/JAX)

Nice to have:Tabular foundation models

Last updated Oct 6, 2026. Interested? Apply on the company site.

About PostEra

Medicinal Chemistry powered by Machine Learning

PostEra is building a modern 21st century biopharma. We're using our advances in machine learning to accelerate Medicinal Chemistry and bring more cures to patients. PostEra advances small molecule programs through partnerships with biopharma while also advancing its own internal pipeline. We've raised $26M from top investors and closed $1Bn in AI partnerships, signing multi-year agreements with Amgen, Pfizer and the NIH. PostEra also launched and led the world's largest open-science drug discovery effort; COVID Moonshot.

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