Job Description

Pfizer's Machine Learning and Computational Sciences group seeks a Senior Machine Learning Scientist to lead research in computational antibody design and optimization. The role combines machine learning, protein science, and therapeutic discovery to accelerate biologic drug development, with emphasis on generative modeling and multi-objective optimization.

Responsibilities

• Conduct original research in computational antibody engineering using sequence and structure-based generative modeling
• Develop and deploy state-of-the-art ML methods for multi-objective antibody optimization balancing affinity, stability, and developability
• Apply proprietary computational frameworks to predict antibody properties and inform rational design
• Collaborate with computational and experimental researchers to identify challenges and integrate computational chemistry and deep learning solutions
• Communicate computational models and algorithms to diverse scientific audiences and publish findings in high-impact journals

Requirements

• Ph.D. in computational chemistry, physical or biological sciences, chemical engineering, computer science, or related field
• Strong background in protein language models and structure-aware predictive and generative modeling
• Proficiency in Python and modern ML libraries (NumPy, SciPy, scikit-learn, PyTorch)
• Experience with compute-intensive ML workloads including GPU acceleration and HPC environments
• Demonstrated ability to conduct independent research and publish scientific work
• Familiarity with sequence analysis and protein structure modeling concepts and tools

Compensation: $106,000-$176,600 base salary, plus 15% bonus target and long-term share-based incentives

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