CMC Scientist/Technical Development Subject Matter Expert - AI Model Evaluation

Volga Partners

8d•$25 - $50•Remote

About The Position

Volga Partners is seeking experienced CMC Scientists and Technical Development professionals to evaluate AI-generated pharmaceutical content. The role assesses the quality, accuracy, completeness, consistency, and scientific validity of content concerning pharmaceutical development, formulation, manufacturing, and technical operations. Evaluators identify inaccuracies and unsupported conclusions, assess scientific reasoning, validate information against applicable FDA requirements, ICH guidelines, pharmaceutical science, and industry practices, and provide clear, structured feedback to improve AI model performance. This is not a traditional pharmaceutical development role: it does not involve developing formulations, conducting laboratory research, overseeing technology transfers, or supporting commercial manufacturing operations. Assignments are completed independently through designated online platforms and follow project-specific criteria, scoring guidelines, quality standards, and timelines. The work is remote and project-based, with variable, potentially irregular or intermittent task availability. Hours and future assignments are not guaranteed. Qualified candidates may need to complete screening questions and evaluation exercises before selection. The primary location is the United States, though professionals elsewhere may be considered if they have substantial U.S. pharmaceutical industry experience. Compensation is hourly and project-based, with the posting listing $25–$50 USD per hour for this role. Rates may vary according to specialization, experience, qualifications, location, assignment requirements, and task complexity.

Requirements

At least 4 years of professional experience in Pharmaceutical Development, Technical Development, Formulation Development, Process Development, Manufacturing Sciences, or related CMC functions.
Bachelor's degree or higher in Pharmaceutical Sciences, Pharmacy, Chemistry, Biochemistry, Chemical Engineering, Biotechnology, Biomedical Engineering, Life Sciences, or a related discipline.
Experience supporting drug substance and/or drug product development activities.
Experience with formulation, process development, technical operations, or manufacturing sciences.
Understanding of pharmaceutical product development lifecycle activities.
Familiarity with FDA regulations and relevant ICH guidelines, including development-related expectations.
Experience interpreting scientific, technical, and manufacturing data.
Ability to critically evaluate scientific and technical information.
Strong analytical, research, and problem-solving skills.
Excellent written English communication skills.
Ability to work independently and follow detailed review instructions.
Comfort working within a task-based freelance engagement model.

Nice To Haves

PharmD, MS, MBA, or PhD.
Experience with oral solid dosage, sterile, injectable, biologic, vaccine, or combination product development.
Experience supporting technology transfer activities.
Experience with process characterization, process optimization, or manufacturing scale-up.
Knowledge of Quality by Design (QbD) principles and control strategy development.
Experience with stability studies, comparability assessments, and product lifecycle management.
Experience collaborating with Regulatory Affairs, Quality, Manufacturing, and Analytical Development teams.
Experience with technical writing, development reports, or scientific document review.
Familiarity with AI evaluation, data annotation, or quality review activities.
Experience with AI model evaluation, large language models (LLMs), research, or structured quality assessments.

Responsibilities

Evaluate AI-generated pharmaceutical content for scientific and technical accuracy, completeness, consistency, and alignment with industry standards.
Review content concerning formulation development, process development, manufacturing science, technology transfer, scale-up, and commercialization.
Assess whether AI-generated conclusions are supported by pharmaceutical sciences, engineering principles, development methodologies, and industry best practices.
Identify unsupported claims, technical inaccuracies, flawed development approaches, and missing scientific context.
Validate information using applicable FDA requirements, ICH guidelines, pharmaceutics principles, and accepted pharmaceutical development practices.
Explain evaluation findings and recommend technically accurate corrections or improvements.
Apply project-specific evaluation criteria, scoring guidelines, and quality standards to support AI quality improvement.
Complete independent evaluations on designated online platforms accurately and within project timelines.