Data Scientist – AI Applications Engineer

Overview

Level 4 AI Engineer role focused on developing and deploying AI-enabled workflow capabilities for Process Development. You will prepare scientific data, implement ML/generative AI components, evaluate performance, and document results.

What you'll do

• Turn defined requirements into AI-enabled data and workflow components for Process Development.
• Clean, transform, and integrate structured and unstructured scientific data and metadata.
• Implement retrieval, automation, context, or human-in-the-loop components using established designs and standards.
• Develop and evaluate ML, generative AI, retrieval-augmented generation, or decision-support approaches using benchmarks and error analysis.
• Build maintainable Python code, notebooks, scripts, pipelines, or services with version control, testing, review, documentation, and reproducibility.
• Support agile delivery activities including requirements clarification, backlog refinement, planning, demos, and feedback collection.
• Document and communicate methods, assumptions, model/agent behavior, limitations, and test evidence to technical and non-technical stakeholders.

What you'll need

• Master's or Bachelor's degree and minimum 4 years of related experience in a relevant technical field.
• Hands-on Python programming experience for data analysis, modeling, automation, or application development.
• Experience preparing, cleaning, exploring, and integrating structured or unstructured data for analytical or ML use cases.
• Experience with machine learning, generative AI, retrieval-augmented generation, workflow automation, or decision-support systems.
• Experience applying evaluation methods including train/test design, performance metrics, benchmark execution, error analysis, and quality checks.
• Familiarity with software engineering practices such as version control, code review, testing, documentation, and reproducible workflows.

Details

• Collaborate across time zones with AIN and U.S. TDC partners in a matrixed global environment.