AI/ML Biopharma Deployment Consultant (contract)

Atrium Works•Boston, MA

4d•Onsite

About The Position

We are seeking a consultant to partner with Biopharmaceutical Sciences and Manufacturing teams to develop and implement an enterprise AI/ML strategy that accelerates biologics and cell therapy CMC development. The role will deliver near-term productivity improvements through AI tools, copilots, agents, and employee enablement; develop a longer-term roadmap for AI-enabled laboratory and manufacturing transformation; and support execution of an automated laboratory pilot.

Requirements

MS or PhD in Biotechnology, Engineering, Data Science, Computer Science, or related discipline.
5+ years of experience in biopharmaceutical development, laboratory automation, AI/ML, or related fields.
Strong knowledge of biologics and/or cell therapy CMC development.
Experience with laboratory automation, robotics, ELN/LIMS, data integration, and scientific data analytics.
Demonstrated experience applying AI/ML to scientific, engineering, or manufacturing challenges.
Understanding of Agentic AI frameworks, workflow orchestration, autonomous agents, and human-in-the-loop governance models.
Ability to bridge scientific, technical, and business stakeholders to drive adoption and implementation of AI-enabled solutions.
Strong understanding of data governance principles, data architecture, ontology, data quality management, and enterprise AI governance.
Familiarity with regulatory expectations and industry best practices related to AI deployment in GxP, GMP, pharmaceutical, biotechnology regulated environments.

Responsibilities

Develop a strategic roadmap for AI/ML deployment across Biopharmaceutical Sciences and Manufacturing functions.
Identify high-value use cases for AI, machine learning, automation, and advanced analytics within Process Development, Analytical Development, Manufacturing Sciences, and technical operations.
Develop and deploy high-impact micro-productivity AI tools, copilots, and agents for scientific and operational workflows, including scientific knowledge retrieval, report and protocol drafting, literature synthesis, data interpretation, technical documentation, regulatory-response support, and project management.
Develop and deploy AI-enabled laboratory automation, data-driven experimentation, and closed-loop development platforms that connect automated equipment, analytical systems, and advanced AI/ML models.
Develop a roadmap for macro-productivity improvement through AI-enabled manufacturing technologies, including advanced process monitoring, multivariate analytics, soft sensors, predictive modeling, anomaly detection, digital twins, advanced process control, and manufacturing workflow optimization.
Support pilot projects and establish a scalable framework for broader enterprise deployment.
Align data, technology, governance, validation, human oversight, and change-management requirements for responsible deployment in regulated environments.