Founded in 1925, Festo Corporation is the leading worldwide supplier of automation technology and the performance leader in industrial training and education programs.  For many years Festo has been providing impetus for factory automation and offers a wide product and service portfolio – from individual components to complex customized solutions and system. As a family-owned company, we act from a holistic perspective. We take responsibility for our actions globally and locally, we want to contribute to the quality of life and conservation of resources where we operate with new technologies, knowledge and education.

At Festo, we hire people who continuously live our five core Values:

• We are Ambitious
• We are Determined
• We are Visionary
• We Value Each Other
• We are Dependable

This internship is a unique opportunity to work with experienced professionals in an innovative and fast-paced engineering environment. We are committed to providing our interns with hands-on, practical experience that will provide a solid foundation for continued growth in their careers.

Our Research Hub in Marlborough is seeking an enthusiastic Co‑op student to support ongoing research and development in AI‑driven Life Science Automation.
In this role, you will contribute to the design, implementation, and evaluation of LLM‑based and agentic AI solutions that enhance engineering workflows, lab automation systems, and Festo’s deep tech development efforts.

You will work closely with cross‑disciplinary teams to conceptualize and prototype software components, explore advanced AI methods for lab and automation environments, and document results to support our innovation roadmap.

Primary Responsibilities

• Conduct applied research on LLM‑based agents for engineering and lab automation, including planning, tool use, workflow orchestration, memory handling, and evaluation.
• Engineer requirements for setting up prototypes.
• Conceptualize and prototype agentic AI solutions (Python preferred) that interface with Festo engineering interfaces, toolchains, and data sources.
• Explore cutting-edge methods for improving the visibility, quality, and reliability of technical information within AI‑generated outputs; derive general recommendations and design supporting experiments.
• Document findings, benchmarks, architecture concepts, and prototypes; communicate results to stakeholders in the company.
• Support positive team interactions and contribute to milestone and schedule commitments within an agile framework.

Required

• Enrolled in a master’s degree in Computer Engineering, Software Engineering, Computer Science, AI/ML, or related field.
• Strong experience with Python and modern AI/ML tooling (e.g., prompting, MCP development, RAG, LLM APIs, PEFT fine‑tuning).
• Strong analytical and problem‑solving skills; structured and outcome-oriented mindset.
• Curiosity for automation and creating functional prototypes from research concepts.
• Excellent communication skills and ability to work in a collaborative team environment.

Additional Requirements / Preferred

• Experience with collaborative version control tools, such as GitHub/GitLab, CI/CD workflows, MLOps, and modern software development processes and tools.
• Familiarity with ML frameworks (e.g., NumPy, Pandas, PyTorch, TensorFlow, scikit‑learn).
• Understanding of machine‑learning concepts such as transformers, embeddings, supervised learning, and evaluation metrics.
• Experience with interfacing systems, APIs, or automation equipment is a plus.
• Self‑motivated and proactive working style.