Ville :

Catégorie : Full time

Industrie : Educational Services

Employeur : University of British Columbia

Staff - Non Union

Job Category

M&P - AAPS

Job Profile

AAPS Salaried - Information Systems and Technology, Level C

Job Title

AI and Data Engineer, VCHRI

Department

AI Hub | Vancouver Coastal Health Research Institute | Faculty of Medicine

Compensation Range

$6,747.50 - $9,701.42 CAD Monthly

The Compensation Range is the span between the minimum and maximum base salary for a position. The midpoint of the range is approximately halfway between the minimum and the maximum and represents an employee that possesses full job knowledge, qualifications and experience for the position. In the normal course, employees will be hired, transferred or promoted between the minimum and midpoint of the salary range for a job.

Posting End Date

March 21, 2026

Note: Applications will be accepted until 11:59 PM on the Posting End Date.

Job End Date

April 19, 2027

 

 

At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career. 

Job Summary
Vancouver Coastal Health Research Institute (VCHRI) is the research arm of Vancouver Coastal Health (VCH) and a close partner of the University of British Columbia (UBC). It is the home of nationally and internationally recognized research centres and programs conducting cutting edge research that aims to improve health outcomes. VCHRI is also known for its breadth and depth of science from bench side to bedside, technology transfer, incubating spinoff companies, and is a central hub for research training, recruitment and retention of future leaders.

The AI & Data Engineer is a critical infrastructure-building role within the VCHRI AI Hub. This is an opportunity focused on laying the department's entire technical groundwork, including the construction of a new, secure development environment on the university cloud. The engineer will transition abstract research needs into robust engineering solutions by evaluating and implementing the initial stack of open-source tools necessary for processing complex medical data (text, image, video). This role serves as a technical catalyst, rapidly developing Proofs of Concept (POCs) that collaborate with world-class researchers to bridge the gap between theoretical science and practical patient care outcomes.

 

The AI & Data Engineer will champion the implementation and enforcement of robust cybersecurity policies and practices across the portfolio, ensuring compliance with Policy SC14 and the protection of sensitive data and systems. They will collaborate closely with UBC IT Cybersecurity teams to proactively identify and mitigate potential threats, maintaining a secure and resilient digital environment.

Organizational Status
This position is based at the VCHRI University/Hospital site. Reports to the Associate Director, AI & Advanced Analytics, VCHRI. Operates as a primary technical resource, collaborating directly with clinical researchers to translate complex research questions into actionable technical requirements. This role serves as the team's technical voice, responsible for demystifying AI technology for non-technical stakeholders and providing technical guidance on AI governance to ensure alignment with organizational goals.

Work Performed
1. Computing Environment Development & Management

• Takes ownership of establishing and architecting the department’s computing footprint on the university cloud, ensuring a robust foundation for AI research.

• Configures, secures, and maintains Linux-based development environments, utilizing Bash scripting and SSH to manage standard Virtual Machine (VM) environments.

• Design and implements a lean, agile, and secure development ecosystem optimized for rapid experimentation and innovation, avoiding unnecessary enterprise-grade DevOps overhead.

• Ensures the accessibility and reliability of the development environment.

2. Data Engineering & Technology Evaluation

• Acts as a technical scout for the department, continuously scanning and evaluating the rapidly shifting landscape of open-source tools and libraries.

• Tests and validates various open-source technologies to determine the optimal solutions for the department's specific data infrastructure needs.

• Develops recommendations and pipelines for the ingestion, storage, and processing of complex medical data, including tabular records, text, diagnostic images, and video.

3. Rapid Prototyping & Application Development

• Transforms abstract research concepts into functional technical solutions by building POCs and prototypes that demonstrate the value of AI in clinical settings.

• Iterates on prototypes based on feedback and performance evaluations to prove technical feasibility and operational value before full-scale deployment.

• Utilizes Docker for containerization and Git for version control to ensure code quality, reproducibility, and effective collaboration.

4. Technical Consulting & Stakeholder Collaboration

• Serves as the primary technical voice and "AI catalyst" for VCHRI teams, bridging the gap between technical engineering and clinical research.

• Collaborates closely with clinical researchers to translate high-level inquiries and hypotheses into concrete technical requirements and engineering specifications.

• Demystifies complex AI and data technologies for non-technical stakeholders, helping them understand the art of the possible and the capabilities of modern AI tools.

• Provides technical guidance on AI governance, ensuring that technical implementations align with ethical standards and institutional policies.

5. General Responsibilities & Continuous Improvement

• Maintains technical currency by staying up to date with the latest advancements in open-source AI tools, libraries, and best practices.

• Ensures data handling practices align with medical data standards (e.g., DICOM, HL7) where applicable, maintaining strict adherence to security and privacy requirements.

• Documents technical architectures, decision logs regarding tool selection, and user guides to support knowledge transfer and system maintainability.

Consequence of Error/Judgement
This is a builder role fundamental to the foundation of Medical AI at the institute. Decisions made regarding the initial data infrastructure tools and development environment will directly impact the ability of researchers to unlock the potential of medical data. Errors in technical evaluation or prototype development may delay research intended to improve patient outcomes.

Supervision Received
This role offers high autonomy, giving you significant influence over the technical stack and engineering practices. The incumbent works independently under the general direction of the Associate Director, AI and Advanced Analytics, VCHRI.

Supervision Given
None.

Minimum Qualifications
Undergraduate degree in a relevant discipline. Minimum of three years of related experience, or the equivalent combination of education and experience.

- Willingness to respect diverse perspectives, including perspectives in conflict with one’s own

- Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion

Preferred Qualifications

• Understanding of foundational ML concepts and practical experience using key libraries (e.g., PyTorch, Hugging Face, or scikit-learn) for rapid prototyping and development.

• Post-graduate university degree in Computer Science, Engineering, Health Informatics, Data Science, or a related discipline.

• Strong, demonstrated proficiency in Python for data engineering or software development applications.

• Demonstrated ability to act as a technical scout, independently experimenting with, and validating new open-source tools and libraries to determine their suitability for data infrastructure and AI development needs.

• Fluent with Azure Databricks and the broader Azure AI ecosystem.

• Solid foundation in Linux administration with the ability to manage standard Virtual Machine (VM) environments. Must be proficient in Bash scripting and using SSH for secure remote management.

• Expertise in version control (e.g., Git) and source code management, along with practical experience using Docker for containerization and reproducible development environments.

• Experience working with medical data standards and systems, specifically DICOM for imaging, HL7 for health data exchange, and PACS (Picture Archiving and Communication Systems) servers.

• Excellent communication skills with the ability to bridge the gap between technical engineering and research.

• Experience architecting secure, accessible development environments from scratch on university or private cloud infrastructure.

• Demonstrated experience designing end-to-end data architectures specifically supporting AI and Machine Learning applications.