Senior Scientist, Machine Learning

Candidates local to Seattle are preferred, but remote applicants are welcome to apply. Candidates must reside in the United States.

Starting Salary Range: $166,000 to $208,000 per year

Exemption Status: Exempt

Location Expectations: Remote-Eligible

Role Description

At A-Alpha Bio, we’re on a mission to improve human health by unlocking the potential of protein-protein interactions – and we’re now seeking a Senior Scientist to join our Machine Learning Research team in researching and developing cutting-edge machine learning models trained on proprietary protein-protein interaction (PPI) data for the optimization of biologics.

• As an ML scientist, you’ll research state-of-the-art AI algorithms — protein language models, generative AI, and geometric deep learning — that unravel the intricacies of protein-protein interactions to advance our technology and power our in-house drug discovery pipeline.
• As an ML engineer, you’ll develop a robust and extensible code base, advocate for software best practices, ensure data integrity, and deploy scalable models in cloud computing environments.
• As a mentor, you’ll closely collaborate and serve as a role model for a team of world-class ML scientists, helping to raise the bar for research and increase team-wide technical expertise.

Key Responsibilities

• Design and implement novel machine learning approaches for prediction and engineering of protein-protein interactions; use these approaches to solve challenges in drug discovery and optimization.
• Generate deliverables (e.g., new code features, research reports, presentations, and data sets) to a high level of quality suitable for broad consumption within the company, as well as in accordance with assigned timelines.
• Regularly and expertly contribute to the company codebase, authoring and reviewing merge requests and ensuring that new capabilities are effectively rolled out to the rest of the team.
• Enthusiastically collaborate with the Machine Learning team, providing coaching, mentorship, and subject matter expertise to members of the broader Data Science department.
• Perform other duties as assigned.

Qualifications & Experience

Required

• Bachelor’s degree in a related field with 6+ years of professional experience in machine learning, including 3+ years of direct experience with machine learning using biological sequence or protein structure data; or an equivalent combination of education and experience.
• Extensive experience with deep learning, spanning use of modern software frameworks (PyTorch, TensorFlow, PyG); adapting, modifying, or originally developing model architectures (CNNs, VAEs, Transformers, graph neural networks); as well as familiarity with state-of-the-art generative AI approaches (diffusion, language models)
• Deep understanding of underlying theory and mathematics for machine learning and ability to translate and implement it into code.
• Strong expertise in data science and experience with manipulating/transforming data, model selection, model training, cross-validation, and deployment at scale.
• Familiarity with scientific concepts in biochemistry, physical chemistry, molecular physics, and biology.
• Excellent skills in communicating research results with both technical and non-technical audiences.

Preferred

• PhD in a related field.
• Domain expertise with Python and Amazon Web Services (or other cloud provider, such as Azure, GCP).
• Familiarity with developing, deploying, and maintaining machine learning engineering systems for model training and inference, including aspects of CI/CD, MLOps, distributed computing, and/or data engineering.
• Familiarity with the state of the art in antibody engineering, protein engineering, synthetic biology, or other high-throughput biology environments.
• A record of scientific research publications and/or presentations in top-tier journals and conferences.

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