Hybrid Applied AI – Graduate Intern

at EnerSys

• Job title: Applied AI – Graduate Intern
• Job type: Internship
• Experience level: Entry level
• Salary: $35 - $40 per hour
• Degree requirement: Postgraduate Degree
• Tech skills: Numpy, Pandas, Python, PyTorch
• Location requirements: Hybrid, Anytown, United States

About the role

• Intern contributing to design, development, and evaluation of AI applications in energy. Engaging with projects on intelligent workflow automation and LLM applications in various contexts.

Responsibilities

• Design and implement agentic AI architectures, including multi-agent workflows, tool-calling systems, memory and state management, and orchestration logic for complex multi-step tasks.
• Develop and evaluate retrieval-augmented generation (RAG) pipelines, with attention to retrieval strategy, document chunking and indexing, embedding model selection, re-ranking, and end-to-end evaluation.
• Contribute to LLM evaluation and validation frameworks — defining test coverage, constructing evaluation datasets, assessing output reliability, and identifying failure modes through structured testing and adversarial analysis.
• Conduct prompt engineering and instruction design for domain-specific tasks, and support experimentation with parameter-efficient fine-tuning approaches where applicable.
• Perform model benchmarking and comparative analysis, including evaluation of commercial and open-source LLMs for specific task types, latency and cost tradeoffs, and domain adaptation requirements.
• Support integration of LLM and agentic components with broader system architectures, including data pipelines, APIs, and domain-specific tooling.
• Contribute to data preparation and preprocessing workflows for structured and unstructured industrial datasets, including cleaning, transformation, and schema design.
• Engage in the full engineering rigor expected of production AI/ML systems — including unit and integration testing, model verification and validation, experiment evaluation, simulation workflows, data and output visualization, and technical documentation and reporting — as continuous activities throughout the project lifecycle.

Requirements

• Currently enrolled in a Master's or PhD program in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or a closely related discipline — or recently graduated from such a program.
• Strong theoretical foundation in machine learning and deep learning, with the ability to reason about model behavior, generalization, and failure modes.
• Demonstrated hands-on experience building LLM-based applications — including at least one of the following: agentic systems, RAG pipelines, structured output generation, or tool-augmented language models.
• Proficiency in Python; fluency with ML frameworks, particularly PyTorch.
• Strong data handling and analysis skills — experience working with complex, real-world datasets using pandas, NumPy, or equivalent tools.
• Ability to design and execute rigorous experiments, interpret results critically, and communicate findings clearly in written and verbal form.

Benefits

• Paid time off plus paid holidays
• Medical/dental/vision insurance plan
• Life insurance, short/long term disability, tuition reimbursement, flex spending, and employee stock purchase plan
• 401K plan