Job description

Job Location MASON BUS AND INNOVATION CTR Job Description Research and Development (R&D) at Procter & Gamble, the largest consumer packaged goods company in the world, includes a diverse group of roles that contribute to the innovation and development of our products. It encompasses roles in product research, formulation, testing, and scientific analysis. You will find variety and excitement starting Day 1. This internship is specifically designed for individuals working towards a PhD who are developing proficiency in their field. As an intern or co-op in management, you will have the opportunity to learn from experienced professionals in a supportive environment. This is a 12-week paid internship, designed to provide you with a solid foundation for future career growth. The internship will take place from May (potentially early June) to August of 2027. Join us at P&G, where your contributions will play a vital role in shaping the future of consumer products! The Opportunity: P&G has an opportunity for a PhD intern to work in our Corporate R&D to develop an AI-agent-driven framework that automates and accelerates machine learning experimentation for time-series data modeling. The intern will explore how AI agents can propose and execute experiments, modify configurations or code, analyze results, and recommend next steps. This work will investigate improvements in data preprocessing, model architecture, training strategies, and hyperparameter selection while comparing AI-driven research with conventional experimentation in terms of model performance, reproducibility, and research efficiency. The ideal candidate will demonstrate a strong eagerness to learn and grow professionally and possess excellent communication skills—both written and verbal. This role is perfect for those with passion for innovation and problem-solving, along with a proactive attitude and the ability to adapt to new challenges. Join us in this dynamic environment, where your contributions will make a real impact as part of a collaborative team! Key Responsibilities: Review existing literature and techniques in LLM-based AI agents, automated machine learning, and AI-enabled research systems. Prepare time-series datasets and establish a reliable, reproducible baseline model and evaluation pipeline. Design and implement an AI-agent-driven framework for proposing, executing, and analyzing machine learning experiments. Explore improvements in data preprocessing, feature representation, model architecture, training strategies, and hyperparameter selection. Implement appropriate validation, experiment-tracking, and reproducibility practices for AI-generated configurations or code. Compare AI-enabled and conventional experimentation approaches based on model performance, reproducibility, experiment throughput, and research efficiency. Document the framework, experiments, results, limitations, and recommendations. Share key insights and present final results to the broader R&D team. Job Qualifications Required Qualifications: Education: Working towards a PhD in Computer Science, Computer Engineering, Data Science, Electrical Engineering, Statistics, or a related field. Experience developing and evaluating machine learning or deep learning models. Hands-on experience with a deep learning framework such as PyTorch or TensorFlow. Proficiency in Python. Understanding of model training, validation, performance evaluation, and experimental design. Ability to review technical literature, formulate research hypotheses, and translate ideas into reproducible experiments. Available to work a 12-week internship from May/early June to August in the summer of 2027. Available to work 5 days a week in office at Mason, OH location. Preferred Qualifications: Experience with large language models, generative AI, and the design of multi-step agentic workflows or multi-agent systems. Experience with agentic frameworks such as LangGraph and AI observability platforms such as Arize. Experience with automated machine learning, hyperparameter optimization, experiment orchestration, or experiment-tracking systems. Experience in time-series data modeling. A record of research contributions through grants, fellowships, patents, peer-reviewed publications, conference presentations, or relevant open-source projects. Just so you know: At P&G, we believe that diverse experiences help build strong leaders. Mobility is a key component of many management careers, providing opportunities to grow through different assignments, locations, and business challenges. Candidates should be prepared to consider relocation opportunities throughout their career as business needs and development opportunities arise. Compensation for roles at P&G varies depending on a wide array of non-discriminatory factors including but not limited to the specific office location, role, degree/credentials, relevant skill set, and level of relevant experience. At P&G compensation decisions are dependent on the facts and circumstances of each case. Total rewards at P&G include salary bonus (if applicable) benefits. Your recruiter may be able to share more about our total rewards offerings and the specific salary range for the relevant location(s) during the hiring process. We are committed to providing equal opportunities in employment. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Immigration Sponsorship is not available for this role. For more information regarding who is eligible for hire at P&G along with other work authorization FAQ’s, please click HERE . Procter & Gamble participates in E-Verify. Qualified individuals will not be disadvantaged based on being unemployed. P&G is dedicated to meeting the needs of applicants requesting an accommodation/adjustment due to a disability in order to complete the online application process. If you have a disability that affects your ability to complete our online application process, please visit our Disability Accommodation Page . Job Schedule Full time Job Number R000158985 Job Segmentation Internships Starting Pay / Salary Range $60.57 - $60.57 / hour

Requirements

Must-haves

Job Location
Review existing literature and techniques in LLM-based AI agents, automated machine learning, and AI-enabled research systems.
Prepare time-series datasets and establish a reliable, reproducible baseline model and evaluation pipeline.
Design and implement an AI-agent-driven framework for proposing, executing, and analyzing machine learning experiments.
Explore improvements in data preprocessing, feature representation, model architecture, training strategies, and hyperparameter selection.
Implement appropriate validation, experiment-tracking, and reproducibility practices for AI-generated configurations or code.
Compare AI-enabled and conventional experimentation approaches based on model performance, reproducibility, experiment throughput, and research efficiency.
Document the framework, experiments, results, limitations, and recommendations.
Share key insights and present final results to the broader R&D team.
Job Qualifications
Education: Working towards a PhD in Computer Science, Computer Engineering, Data Science, Electrical Engineering, Statistics, or a related field.
Experience developing and evaluating machine learning or deep learning models.
Hands-on experience with a deep learning framework such as PyTorch or TensorFlow.
Proficiency in Python.
Understanding of model training, validation, performance evaluation, and experimental design.
Ability to review technical literature, formulate research hypotheses, and translate ideas into reproducible experiments.
Available to work a 12-week internship from May/early June to August in the summer of 2027. Available to work 5 days a week in office at Mason, OH location.
Immigration Sponsorship is not available for this role. For more information regarding who is eligible for hire at P&G along with other work authorization FAQ’s, please click HERE .
Procter & Gamble participates in E-Verify.

Nice-to-haves

Experience with large language models, generative AI, and the design of multi-step agentic workflows or multi-agent systems.
Experience with agentic frameworks such as LangGraph and AI observability platforms such as Arize.
Experience with automated machine learning, hyperparameter optimization, experiment orchestration, or experiment-tracking systems.
Experience in time-series data modeling.
A record of research contributions through grants, fellowships, patents, peer-reviewed publications, conference presentations, or relevant open-source projects.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningllmpython

Platform: workday
Effort: long