Senior Scientist, Computational Biotherapeutics Engineering

Pfizer

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Cambridge, MA
Employment: Full-time
Posted: 152 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $210k

$154k $264k

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This listing doesn't post a salary. Most similar roles pay $177,250–$241,906.

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About Pfizer

Pfizer Inc. is one of the world''s largest biopharmaceutical companies, researching, developing, manufacturing, and marketing medicines and vaccines across multiple therapeutic areas including oncology, cardiology, and infectious diseases. Industry: Biopharmaceuticals

Pfizer currently has 8 open roles on FindRole.

Listed pay typically runs $122,550–$204,250 across 6 roles with salary data.

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At a glance

TL;DR · Senior Scientist, Computational Biotherapeutics Engineering

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JOB TITLE: Senior Scientist, Computational Biotherapeutics Engineering The Senior Scientist, Computational Biotherapeutics Engineering joins the BioMedicine Design department to work within a computational team focused on the discovery and optimization of industry-leading biotherapeutics. This role involves implementing and evaluating state-of-the-art AI/ML methods to advance biotherapeutic discovery and engineering, specifically integrating new models into scalable discovery workflows. Key responsibilities include developing workflows for computational protein design, training models for antibody developability engineering, and analyzing large-scale sequence and structure datasets to link protein features to pharmaceutical properties. The position requires expertise in Python, PyTorch, and scientific libraries like NumPy and scikit-learn. Candidates will utilize deep learning architectures, including transformer and diffusion-based approaches, to solve complex problems in protein representation, structure prediction, and generative design within HPC or cloud computing environments.

Skills

AI/ML Python PyTorch NumPy SciPy scikit-learn Deep Learning NLP Generative AI AWS Google Cloud HPC Slurm Protein Language Models AlphaFold RFdiffusion Rosetta Schrödinger MOE FoldX Bioinformatics

What you'll do

Implement advanced AI and machine learning workflows for computational protein design in HPC or cloud environments.
Design and train AI/ML models specifically for antibody developability engineering and lead optimization.
Integrate new AI models into scalable discovery workflows to support biotherapeutic design and decision-making.
Analyze large-scale sequence, structure, and experimental datasets to link protein features to pharmaceutical properties.
Serve as a technical expert on deep learning models for protein sequence and structure to support discovery teams.
Communicate complex scientific ideas and model limitations to both technical and non-technical audiences.
Optimize the computational developability platform by collaborating with computational and wet lab experts.

What we're looking for

PhD in a relevant field with experience, a Master's with , or a BA/BS with .
Demonstrated track record of using AI/ML-driven protein modeling and design to influence project strategy.
Hands-on experience using modern AI/ML models for protein representation, structure prediction, or generation.
Strong understanding of protein structure, sequence-structure relationships, and model evaluation.
Experience programming in Python using libraries like NumPy, SciPy, scikit-learn, and PyTorch.
Experience working with large biological datasets and bioinformatics resources.
Permanent work authorization in the United States.
Experience with protein language models, generative structure models, or structural prediction AI models (preferred).

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