If you are interested in applying Large Language Models (LLMs) and Natural Language Processing (NLP)to address real-world challenges in industrial operations, this is a perfect opportunity. Youll work on automatically analyzing contracts and agreements, extracting billing rules, validating transactional data against those rules, and generating recommendations to resolve discrepancies. Be part of a team developing AI/ML methods that improve billing accuracy and operational efficiency, while being mentored by some of the best minds in AI.

- Subhojeet Pramanik, Machine Learning Scientist

About the Role

This is a paid Residency that will be undertaken over a twelve-month period with the potential to be hired by our client afterwards (note: at the discretion of the client). The Resident will be reporting to an Amii Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities.

About our Client

VistaVu Solutions is a leading provider of business management software for mid-market companies across North America. An award-winning SAP partner, VistaVu specializes in SAP Business One, SAP Business ByDesign, and SAP S/4HANA Cloud. They bring deep expertise in industries such as wholesale distribution, manufacturing, aerospace & defense, and field services. Their integrated ERP solutions, custom extensions, and advanced applications help customers streamline operations, enhance productivity, and RUN GREAT. Proudly employee-owned, VistaVu is committed to continuous innovation, cultivating a positive workplace culture, and making a meaningful impact in the communities where they and their customers live and work.

About the Project

This project focuses on developing an AI-powered solution to extract and apply complex billing rules from unstructured contracts and agreements using large language models (LLMs). The LLMs will identify and extract structured rules related to time, equipment, materials, and third-party charges, enabling automated validation of transactions in systems like SAP and FieldVu prior to invoicing the end customer. The goal is to catch discrepancies early, reduce manual reconciliation, accelerate customer payments, and minimize financial write-offs. Key components include a rule extraction pipeline, metadata tagging, and a validation engine, designed for scalability across the field services industry.

Who Are You

You have completed a graduate-level program or higher (M.Sc/Ph.D) in Computing Science, ML, or Engineering, with substantial research or project experience in machine learning, deep learning, and/or time series analysis. You are proficient in Python and familiar with key ML frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, and Pandas. Your positive attitude towards learning new applied domains and your ability to communicate technical concepts clearly make you a valuable team player. You are enthusiastic about collaborating across interdisciplinary teams to achieve excellence.

What You Will Be Doing

In this role, you will be instrumental in developing machine learning models, specifically leveraging Large Language Models (LLMs) and Natural Language Processing (NLP), for automating the extraction of contractual rules and verifying their consistent application to timesheets and purchase orders. Your work will focus on analyzing contractual documents to extract rules in both machine-readable logical representations and human-readable descriptions, identify discrepancies between these rules and transactional data, classify gaps, and generate actionable recommendations. You will explore and implement LLM techniques including prompt engineering and potential fine-tuning. You will be responsible for data preparation, including document loading, splitting, metadata extraction, and annotation, as well as managing a database of extracted rules. You will collaborate with interdisciplinary teams, participate in project meetings, and contribute to reports on model performance and project milestones. Your efforts will directly contribute to shifting the current manual validation process to an automated strategy, reducing manual effort, improving accuracy, and enhancing overall operational efficiency.

Required Skills / Expertise

Were looking for a talented and enthusiastic individual with solid knowledge of machine learning, demonstrated experience with supervised learning, and experience in applied settings.

Key Responsibilities:

• Design, implement, optimize, and evaluate machine learning models, specifically leveraging Large Language Models (LLMs), tailored for automating the extraction of contractual rules and verifying their consistent application to timesheets and purchase orders, with a specific focus on developing, training, and refining solutions for analyzing contractual documents.
• Prepare and curate high-quality, text datasets, including document loading, splitting, metadata extraction, and annotation, for model training and validation from diverse sources.
• Utilize state-of-the-art machine learning frameworks and tools, including TensorFlow, PyTorch, Scikit-learn, Spacy, and Pandas, to enhance model performance and streamline data processing and rule management in a database.
• Collaborate with cross-functional teams to build and deploy solutions that address client needs, ensuring seamless integration into existing systems.
• Engage in regular client meetings, contributing insights and updates on model performance and project milestones through presentations and detailed reports.
• Optimize machine learning pipelines to ensure efficient and scalable text analysis capabilities, leveraging techniques like prompt engineering, Natural Language Processing (NLP) and potential fine-tuning of Large Language Models (LLMs).

Required Qualifications:

• Completion of a graduate level program or higher (M.Sc/Ph.D) in Computing Science, ML or Engineering
• Research or project experience in text analysis, information retrieval, and natural language processing use cases
• Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, TensorFlow, PyTorch, Pandas)
• A positive attitude towards learning and understanding a new applied domain
• Must be legally eligible to work in Canada

Preferred Qualifications:

• Previous experience applying machine learning and Natural Language Processing (NLP) to text data for information extraction, rule extraction, and extracting structured information from unstructured documents.
• Experience with Large Language Models (LLMs), prompt engineering, and fine-tuning.
• Familiarity with document analysis, text processing challenges, and document metadata extraction.
• Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.

Non-Technical Requirements:

• Desire to take ownership of a problem and demonstrated leadership skills
• Interdisciplinary team player enthusiastic about working together to achieve excellence
• Capable of critical and independent thought
• Able to communicate technical concepts clearly and advise on the application of machine intelligence
• Intellectual curiosity and the desire to learn new things, techniques, and technologies

Why You Should Apply

Besides gaining industry experience, additional perks include:

• Work under the mentorship of an Amii Fellow and Amii Scientist for the duration of the project
• Participate in professional development activities
• Gain access to the Amii community and events
• Build your professional network
• The opportunity for an ongoing machine learning role at the clients organization at the end of the term (at the clients discretion)

About Amii

One of Canadas three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the worlds top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

How to Apply

If this sounds like the opportunity you've been waiting for, please dont wait for the closing June 27, 2025 to apply - were excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and wont be used in the selection process.