Technical Specialist, MLOps Engineer
Technical Specialist, MLOps Engineer
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Job Description
Union: Non-Union
Number of Vacancies: 1
Site: 200 Elizabeth St Toronto ON M5G 2C4
Department: AI Collaborative Centre
Reports to: Chief AI Scientist
Work Model: Hybrid (3 days on site)
Hours: 37.5 Per Week
Shifts: Monday to Friday
Status: Temporary Full-Time
Closing Date: August 5 2025
Position Summary:
Join the forefront of AI-driven health care innovation as a Technical Specialist MLOps Engineer at the University Health Network (UHN) AI Hub where cutting-edge technology meets life-changing impact. Work alongside top scientists clinicians and researchers to design and develop sophisticated ML pipelines agent systems and deployment platforms driving advancements in cancer care and beyond. In this dynamic role youll apply MLOps methodologies to solve complex health challenges optimize hospital operations and pioneer groundbreaking AI solutions. If youre passionate about transforming data into responsible AI-driven breakthroughs this is your opportunity to lead the way!
Duties:
- Develop and manage data processing ML pipelines and agent systems to support AI-driven health care innovations. This involves pre-processing cleaning and organizing multi-modal data for data pipelines and AI integration.
- TECDeploy monitor and optimize machine learning models in clinical environments and processes to ensure seamless integration and efficiency. Set up monitoring tools to monitor AI performance and track various metrics such as response time errors and resource utilization.
- Collaborate with clinicians and researchers to design secure data pipelines and implement responsible AI applications. Regularly document your findings and methodologies. Publish in peer-reviewed journals and present at conferences.
- Apply MLOps methodologies to enhance hospital efficiency streamline workflows and improve patient care.
- Ensure compliance with ethical AI standards and contribute to the development of safe and responsible AI practices in healthcare.
- Provide technical expertise and mentorship to research teams students and clinicians working on AI-related projects.
- Stay ahead of emerging AI trends by continuously learning and integrating cutting-edge technologies into UHNs AI ecosystem.
Qualifications :
- Undergraduate degree graduate would be an asset in engineering computer science or related disciplines.
- Minimum 5 years related experience required.
- Excellent communication skills and ability to utilize a collaborative approach to solving challenging problems.
- Experience with MLOps enterprise application development implementing and maintaining ML and NLP models IT administration and support.
- Experience with Python (scikit-learn Pandas etc.) and deep learning frameworks (TensorFlow or PyTorch).
- Experience with healthcare data types topics and scientific challenges and approaches.
- Familiarity with HPC environment and running applications in HPC clusters.
- Demonstrate ability to mentor others and work collaboratively with clinicians.
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 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.)
Current UHN employees must have successfully completed their probationary period have a good employee record along with satisfactory attendance in accordance with UHNs attendance management program to be eligible for consideration.
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.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
