Technical Specialist

Company Description

The University Health Network, where “above all else the needs of patients come first”, encompasses Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute and the Michener Institute of Education. The breadth of research, the complexity of the cases treated, and the magnitude of its educational enterprise has made UHN a national and international resource for patient care, research and education. With a long tradition of ground-breaking firsts and a purpose of “Transforming lives and communities through excellence in care, discovery and learning”, the University Health Network (UHN), Canada’s largest research teaching hospital, brings together over 16,000 employees, more than 1,200 physicians, 8,000+ students, and many volunteers. UHN is a caring, creative place where amazing people are amazing the world.

Job Description

Union: Non-Union
Site: Toronto General Hospital
Department: UHN Digital
Reports to: AI Hub Lead
Work Model: Hybrid
Grade: H0:08
Hours: 37.5 hours per week
Salary: $43.37 to $54.21 hourly
Shifts: Monday to Friday
Status: Temporary Full Time (1 year)
Closing Date: May 31, 2024

Position Summary
We are looking for a Technical Specialist with health care and Dev Ops experience to join our University Health Network (UHN) Collaborative Centre for Artificial Intelligence (AI) and Data Science to work with the cancer program. The UHN AI Hub brings together scientists and clinicians from across UHN working to develop and implement safe and responsible applications of AI to improve health care. This role involves working in close collaboration with care providers, researchers and students to build deep expertise and support the MLOps of advance novel applications of artificial intelligence methods to facilitate research and translation into clinical practice.  

The Technical Specialist will design and develop highly sophisticated ML pipelines, deployment platforms and methodologies to support high priority initiatives with cutting edge AI technology within the UHN network. The Technical Specialist works closely with the Chief AI Scientist and team to apply MLOps methods to solve complex health related questions, improve hospital efficiency and develop new research hypotheses. Primary responsibilities include, but are not limited to deploying, managing and optimizing machine learning models in production environments to ensure smooth integration and efficient operations. The Technical Specialist will collaborate with oncology clinicians and scientists to build data pipelines and securely deploy responsible AI. The Technical Specialist will possess strong technical proficiency, creativity, and strong collaborative skills to contribute towards furthering AI capacity and innovation within UHN.   

Duties

Data Processing and Pipelines: Creating and building robust data pipelines for AI. Working with large datasets of oncology data. This involves preprocessing, cleaning, and organizing data for data pipelines and AI integration. 

Model Implementation and Management: Develop and deploy AI models in a clinical environment. This could include creating new data pipelines and integrating AI models into existing clinical systems and processes. Set up monitoring tools to monitor AI performance and track various metrics such as response time, errors and resource utilization.  

Algorithm Optimization: Work with data science specialists to fine-tune algorithms for deployment. 

Collaborative Research: Work closely with biologists and clinicians to understand their data needs and translate these into computational tasks. 

Publishing and Documentation: Regularly document your findings and methodologies. Publish in peer-reviewed journals and present at conferences. 

Grant Writing: Assist in writing grant proposals for funding research projects. 

Mentoring and Supervision: Guide junior researchers or students in their projects, providing expertise in oncology data analysis. 

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-l