Company Description UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. With 10 sites and more than 44,000 TeamUHN members, UHN consists of Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, The Michener Institute of Education and West Park Healthcare Centre. As Canada's top research hospital, the scope of biomedical research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. UHN has the largest hospital-based research program in Canada, with major research in neurosciences, cardiology, transplantation, oncology, surgical innovation, infectious diseases, genomic medicine and rehabilitation medicine. UHN is a research hospital affiliated with the University of Toronto.

UHN’s vision is to build A Healthier World and it’s only because of the talented and dedicated people who work here that we are continually bringing that vision closer to reality.

www.uhn.ca

Job Description Union: Non-Union

Number of vacancies: 1

Site: Toronto General Hospital

Department: Peter Munk Cardiac Centre

Reports to: Principal Investigator

Hours: 37.5 hours per week

Shifts: Days

Status: Temporary Full-Time

Closing Date: October 3, 2025

The Machine Learning Specialist will contribute to the design and development of highly sophisticated Machine Learning (ML) software solutions, platforms, and methodologies supporting high-priority initiatives within the Peter Munk Cardiac Centre (PMCC). The Machine Learning Specialist will work closely with PMCC AI Scientists, Bioinformaticians, and Clinicians in a team-based approach. Beyond current project support, PMCC is seeking applicants with an interest in building agentic systems capable of autonomous planning, reasoning, and tool use to enhance clinical efficiency, streamline hospital operations, and integrate seamlessly into healthcare workflows. The Machine Learning Specialist will be supported in their work by the PMCC Project Manager, Data Scientists, administrative experts, and program medical leadership.

Duties

• Contribute to the design and development of novel machine learning algorithms, agentic systems, and supporting infrastructure with guidance from project leads.
• Implement and optimize machine learning and deep learning algorithms using Python, TensorFlow, PyTorch, or similar frameworks.
• Support and maintain new and existing applications, ensuring reliability and scalability in clinical settings.
• Conduct data preprocessing, feature engineering, and exploratory data analysis on clinical data.
• Perform quality assurance testing, validation, and monitoring of ML models and pipelines.
• With guidance from senior colleagues, assess bias and patterns of vulnerability in data work.
• Collaborate with researchers both in the AI and healthcare specialties to analyze and interpret AI-generated insights for improving patient care and the efficiency of hospital operations.
• Remain active in building knowledge and stay abreast of the latest methods of ML data and information processing.
• Develops, mentors and coaches’ other colleagues who have expressed interest in ML.

Qualifications

• Bachelor’s Degree in Machine Learning, Statistics, Applied Mathematics, Computer Science, or related quantitative disciplines
• Three to five years of practical or relevant experience.
• Strong programming skills in Python and familiarity with AI/ML frameworks such as TensorFlow or PyTorch.
• Understanding of bias, fairness, and safety considerations in applied AI.
• Experience with healthcare data and research is an asset.
• Knowledge of clinical decision support systems and emerging agentic AI applications in healthcare is a strong advantage.
• Familiarity with agentic frameworks (e.g., LangChain, LlamaIndex, Haystack) and integration of tool-use, memory, and planning capabilities is an asset.
• Hands-on experience with retrieval-augmented generation (RAG), vector databases, and knowledge-grounded AI systems is an asset.
• Familiarity with cloud computing platforms (e.g., AWS, Google Cloud) and high-performance computing environments is a plus.
• Excellent problem-solving skills and ability to work independently and in a team environment.
• Strong analytical and communication skills, with the ability to present research findings effectively.

Additional Information Why join UHN? In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.

• Competitive offer packages
• Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
• Close access to Transit and UHN shuttle service
• A flexible work environment
• Opportunities for development and promotions within a large organization
• Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)

UHN is a respectful, caring, and inclusive workplace. We are committed to championing accessibility, diversity and equal opportunity. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known in advance. Any information received related to an accommodation will be addressed confidentially.

University Health Network thanks all applicants, however, only those selected for an interview will be contacted.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates. Please ensure you check your email regularly.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.