Cmc Ai/ml and Automation Scientist

Eli Lilly · Pharma · Indianapolis, IN

This role focuses on applying AI/ML and automation within Chemical, Manufacturing, and Controls (CMC) disciplines in pharmaceutical R&D. The scientist will derive insights from data, build decision support tools, leverage LLMs to enhance data science workflows, and contribute to developing autonomous laboratories through AI-driven methodologies and lab automation. The primary focus is on data preparation, feature engineering, and potentially building agentic systems for experimental design and execution.

What you'd actually do

  1. Work with scientists across Product R&D to identify and solve problems that can be effectively addressed using a combination of AI/ML and fundamental engineering/science principles
  2. Build decision support tools, templates, dashboards for high frequency decisions that can leverage data science approaches
  3. Seek out opportunities to apply advances in large language models (LLM), and evolving AI tools/methodologies to accelerate development workflows
  4. Contribute to capability development efforts to use AI-driven methodologies to autonomously design, plan screening and data rich experiments.
  5. Develop lab automation protocols to execute closed loop hybrid (experimental and compute) workflows

Skills

Required

  • Ph. D. in Chemical Engineering, Chemistry, Formulation, Analytical Sciences, or related field OR MS in Chemical Engineering, Chemistry, Formulation, Analytical Sciences, or related field with 5+ years’ experience
  • Experience in programming in scripting languages such as Python and learning agility to pick up new languages and tools as needed
  • Familiarity with AI frameworks and tools (e.g. TensorFlow, pyTorch)
  • Experience in working with varied data types (structured and unstructured) and databases
  • At least 3 years experience in applying data science/AI techniques either in research or industry
  • Experience applying LLMs either in research or industry
  • Willingness to work with lab scientists to develop automation solutions
  • Strong analytical and problem-solving skills
  • Excellent written and verbal communication skills. Ability to convey technical concepts to non-experts and collaborate effectively with diverse teams

Nice to have

  • Familiarity with big data technologies (such as Azure/AWS)
  • Familiarity with Agentic AI/AI workflow orchestration
  • Familiarity with Microsoft 365 and data platforms (e.g., PowerBI, Fabric) for building AI-augmented workflows and reporting solutions
  • Experience integrating and visualizing data from diverse sources, including leveraging LLM-powered tools to accelerate insight generation and reduce manual data wrangling
  • Familiarity with data models, ontologies, and controlled vocabularies; experience with CMC specific data models and ontologies is a plus
  • Experience building and managing structured scientific workflows
  • Familiarity in one or more of the domain areas: Unit operation design, process modeling, process equipment selection, data rich experiments, PAT utilization in the laboratory and production facilities, or scale-up methodologies
  • Organic chemistry, chemical synthesis, and route design
  • Drug product formulation platforms
  • Online and offline analytical techniques and process analytical technologies (PAT)
  • Experience working with lab or process automation systems such as DeltaV, Labview or other open source systems
  • Familiarity with automated lab reactors/equipment

What the JD emphasized

  • Experience applying AI/ML within at least one CMC discipline
  • utilizing large language models (LLMs) to improve traditional data science workflows
  • use AI approaches and automation to enable the development of autonomous process and product development laboratories

Other signals

  • applying AI/ML within at least one CMC discipline
  • utilizing large language models (LLMs) to improve traditional data science workflows
  • use AI approaches and automation to enable the development of autonomous process and product development laboratories
  • develop lab automation protocols to execute closed loop hybrid (experimental and compute) workflows