AI/ML Scientist

Bayside Solutions; California (MO); On-site; USD 140,000 - 190,000; Full time

Job summary

Bayside Solutions is seeking a hands-on Contract AI/ML scientist to accelerate project work focused on TCI-ability using protein structure, phenotypic, and multimodal data.

This individual contributor will partner closely with computational biology, data science, translational, and discovery teams to develop, evaluate, and apply machine-learning approaches that turn diverse biological datasets into actionable project insights.

Qualifications

• Advanced degree (M.S. or Ph.D.) in computational biology or related field.
• Hands-on experience applying machine learning to biological data.
• Experience with protein structure data or structure-derived features.

Responsibilities

• Develop and apply ML approaches for defined TCI-ability projects using protein structure data, phenotypic data, and other multimodal biological datasets.
• Curate, harmonize, and quality-control structured and unstructured data from internal and external sources; document data provenance, assumptions, and limitations.
• Build reproducible computational workflows for feature generation, model training, validation, and performance evaluation.
• Integrate protein structural representations with cellular, phenotypic, and other biological modalities to generate testable hypotheses and prioritize follow-up analyses.
• Implement clear, maintainable analysis code and contribute to shared repositories, technical documentation, and handoff materials.
• Collaborate with cross-functional scientists to translate biological questions into tractable computational workplans, milestones, and decision-ready outputs.
• Communicate methods, findings, risks, and recommendations clearly to technical and non-technical stakeholders.
• Support rapid iteration on project-specific prototypes and analyses in a dynamic discovery environment.

Skills

Python

Machine Learning

Data curation

Data analysis

Cross-functional collaboration

Education

MS or PhD in computational biology or related field

Tools

Cloud computing

Linux

Job description

Location: Redwood City, CA - Onsite Role

Job Summary

We are seeking a hands-on Contract AI/ML scientist to accelerate project work focused on TCI-ability using protein structure, phenotypic, and multimodal data. This individual contributor will partner closely with computational biology, data science, translational, and discovery teams to develop, evaluate, and apply machine-learning approaches that turn diverse biological datasets into actionable project insights. The role is time-bound and delivery-oriented, with a strong emphasis on building robust analyses, prototypes, and reusable workflows for defined program needs.

Duties and Responsibilities

• Develop and apply machine-learning and statistical approaches for defined TCI-ability projects using protein structure data, phenotypic data, and other multimodal biological datasets.


• Curate, harmonize, and quality-control structured and unstructured data from internal and external sources; document data provenance, assumptions, and limitations.


• Build reproducible computational workflows for feature generation, model training, validation, and performance evaluation.


• Integrate protein structural representations with cellular, phenotypic, and other biological modalities to generate testable hypotheses and prioritize follow-up analyses.


• Implement clear, maintainable analysis code and contribute to shared repositories, technical documentation, and handoff materials.


• Collaborate with cross-functional scientists to translate biological questions into tractable computational workplans, milestones, and decision-ready outputs.


• Communicate methods, findings, risks, and recommendations clearly to technical and non-technical stakeholders.


• Support rapid iteration on project-specific prototypes and analyses in a dynamic discovery environment.

Requirements and Qualifications

• Advanced degree (M.S. or Ph.D.) in computational biology, bioinformatics, computational chemistry, cheminformatics, computer science, data science, biophysics, quantitative biology, or a related field.


• Demonstrated hands-on experience applying machine learning to biological, chemical, or biomedical data.


• Experience working with protein structure data and/or structure-derived features in a research or drug discovery setting.


• Experience integrating, analyzing, or modeling phenotypic and multimodal datasets.


• Strong programming skills in Python and experience with common scientific computing and machine-learning libraries.


• Ability to build reproducible, well-documented computational workflows and clearly evaluate model performance.


• Strong problem-solving, written communication, and cross-functional collaboration skills.


• Ability to independently execute defined project work and deliver high-quality outputs on an agreed timeline.

Preferred Qualifications

• Experience in oncology, drug discovery, translational research, or pharmaceutical/biotechnology R&D.


• Experience with deep learning methods for protein structure, molecular imaging, or other high-dimensional biological data.


• Familiarity with structural bioinformatics tools, protein representation learning, or structure-based modeling.


• Experience with cloud computing, workflow orchestration, version control, and collaborative software-development practices.


• Prior experience delivering computational analyses or prototypes in a contract, consulting, or fast-paced project environment.

Desired Skills and Experience

Machine learning, artificial intelligence, computational biology, bioinformatics, protein structure analysis, structural bioinformatics, phenotypic data analysis, multimodal data integration, biological data modeling, statistical modeling, feature engineering, model training, model validation, performance evaluation, deep learning, protein representation learning, structure-based modeling, molecular imaging, high-dimensional data analysis, data curation, data harmonization, data quality control, data provenance, hypothesis generation, Python, scientific computing libraries, machine-learning libraries, reproducible computational workflows, workflow orchestration, cloud computing, version control, collaborative software development, prototype development, technical documentation, drug discovery, oncology research, translational research, biotechnology R&D, cross-functional collaboration, stakeholder communication, independent project execution

Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.

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