Senior Life Sciences AI Model Trainer

Norstella; Richmond (VA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical and prescription drug benefits

Health savings accounts

Dental plans and vision benefits

401k retirement plan

Short- and long-term disability

Education benefits

Paid parental leave

Paid time off

Job summary

Norstella seeks a Senior Life Sciences Analyst for AI model training who will bridge deep clinical knowledge with applied AI development. You’ll work with data scientists, ML engineers, and data engineers to calibrate model outputs for quality and clinical reasoning, enabling actionable predictive analytics across client engagements.

You will define evaluation rubrics, supervise model behavior, and contribute to knowledge graphs and taxonomy efforts while coordinating with cross-functional teams

Qualifications

• Graduate degree or equivalent professional experience in life sciences, medical sciences, computer science, or related field.
• 3+ years of professional experience with production-grade life science datasets and AI-enabled applications.
• Experience with structured publishing platforms and data tools; comfort with automation concepts.

Responsibilities

• Evaluate model outputs across clinical, regulatory, and life sciences tasks by rating responses and rewriting outputs.
• Define and maintain evaluation rubrics, quality criteria, and preference dimensions for model outputs.
• Act as expert-in-the-loop for commercialization of life science models with clients and provide ongoing support.
• Collaborate with data scientists to iterate data collection pipelines based on feedback.

Skills

Life sciences domain expertise

AI model evaluation

Cross-functional collaboration

Education

Graduate degree in life sciences (or related field)

Job description

Norstella seeks a Senior Life Sciences Analyst for AI model training who will bridge deep clinical knowledge with applied AI development. You’ll work with data scientists, ML engineers, and data engineers to calibrate model outputs for quality and clinical reasoning, enabling actionable predictive analytics across client engagements.

You will define evaluation rubrics, supervise model behavior, and contribute to knowledge graphs and taxonomy efforts while coordinating with cross-functional teams