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Machine Learning Resident - Client : National Safety Services (12 months)

Join to apply for the Machine Learning Resident - Client : National Safety Services (12 months) role at Alberta Machine Intelligence Institute (Amii)

Machine Learning Resident - Client : National Safety Services (12 months)

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Join to apply for the Machine Learning Resident - Client : National Safety Services (12 months) role at Alberta Machine Intelligence Institute (Amii)

If you are interested in applying machine learning to solve real-world industrial challenges related to occupational health and safety, this is a perfect opportunity for you. Be part of a team developing advanced AI / ML methods to identify gaps, classify overlaps, and generate actionable recommendations, all while being mentored by some of the best minds in AI”

• Maithrreye Srinivasan, 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

National Safety Services Inc. (NSS) is a Canadian consultancy and technology company specializing in occupational health and safety (OHS). With over 200 years of combined industry experience, NSS supports private and public sector organizations in achieving regulatory compliance, reducing risk exposure, and improving operational safety. Their multidisciplinary team delivers services ranging from program audits and risk assessments to training and competency framework design. NSS is now leveraging AI and machine learning to modernize traditional safety management systems and disrupt the contractor management space with scalable, intelligent solutions.

National Safety Is Committed To, And Relies Upon, Their Core Values In Guiding Their Business Decisions, Partnerships, And Talent Selection. All Team Members Are Expected To Exemplify The Following Core Values

Integrity - We value authentic, transparent connections.

Collaboration - Stronger together through collaboration.

Resilience - Meeting adversity with a positive mindset.

Growth Minded - Curious, life-long learners driven to improve.

Respect - We believe that everyone deserves respect.

About The Project

NSS is collaborating with the Alberta Machine Intelligence Institute (Amii) to develop an AI-driven system that semi-automates the review of contractor safety policies and programs. Currently a manual and time-intensive process, this validation effort involves assessing whether contractor-submitted documents align with owner expectations, regulatory standards, and best practices.

The project applies state-of-the-art techniques in natural language processing (NLP), Retrieval-Augmented Generation (RAG), and large language models (LLMs) to analyze unstructured documents, identify policy gaps and overlaps, and generate actionable recommendations. The ML Resident will play a key role in developing this proof-of-concept, working with experts from Amii and NSS to build and iterate on a model that significantly enhances accuracy, consistency, and efficiency in contractor policy evaluation.

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 NLP. 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 developing machine learning models to semi-automate and assist in comparing and validating contractor policies against owner requirements and standard frameworks. Your work will focus on analyzing policy documents to identify overlaps, classify gaps, and generate actionable recommendations. You will explore and implement both retrieval-based methods and classification models. You will be responsible for data preprocessing, including handling ambiguous data, formatting inconsistencies, and linking issues. You will also contribute to the development of strategies for gap definition and defining appropriate classification categories. 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 National Safety Services from a manual process to a semi-automated validation strategy, reducing manual effort, improving accuracy, and enhancing overall operational efficiency.

Required Skills / Expertise

We’re looking for a talented and enthusiastic individual with solid knowledge of machine learning and natural language processing (NLP), demonstrated experience with supervised learning, and experience in applied settings.

Key Responsibilities

• Design, implement, optimize, and evaluate machine learning models tailored for semi-automating the validation of contractor policies for conformance with owner requirements, with a specific focus on developing, training, and refining solutions for analyzing policy documents.
• Prepare and curate high-quality, text datasets for model training and validation from diverse sources.
• Utilize state-of-the-art machine learning frameworks and tools, including TensorFlow, PyTorch, Scikit-learn, and Pandas, to enhance model performance and streamline data processing.
• 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 Retrieval-Augmented Generation (RAG) and 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 / NLP frameworks, libraries, and toolkits (e.g., Scikit-learn, Pandas, TensorFlow, PyTorch, LangChain and Vector Databases).
• 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 to text data for information retrieval problems.
• Experience with Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and transformer-based models.
• Familiarity with document analysis and text processing challenges.
• 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 demonstrate 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.
• Ability to work independently and demonstrate effective time management.

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.
• Gain access to the Amii community and events.
• Build your professional network.
• The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion).

About Amii

One of Canada’s 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 world’s 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 don’t wait for the closing June 27, 2025 to apply - we’re 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 won’t be used in the selection process.

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