Machine Learning Software Engineer

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Compensation Range

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Posting End Date

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

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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

The School of Biomedical Engineering (SBME) at the University of British Columbia (UBC) is a partnership between the Faculties of Applied Science and Medicine, established in 2017. Currently the School has 36 core and joint faculty located on campus and at healthcare research institutes, 400+ undergraduate and graduate students, 20+ administrative staff and several research core service facilities. In addition, SBME will move in 2024/2025 into a new building on campus, which will act as a hub for biomedical engineering activities at UBC and beyond. The School is a nucleus for education and training, research, and innovation in biomedical engineering, creating new knowledge, new academic and training programs, and fostering translation and innovation, aspiring to be a global leader in the field. Its vision is to transform health care outcomes through unconstrained exploration of the best possible integrative solutions across engineering, medicine, and biology.

The computational cancer biology and pathology artificial intelligence team (AI in Medicine Lab) at the University of British Columbia (UBC), seeks a motivated Machine Learning Software Engineer. This position entails implementing machine learning-based analysis infrastructure and software for cancer imaging, drug development, and bioinformatics.

Organizational Status
The position reports to the Principal Investigator or a designate in the AI in Medicine Lab.

Work Performed

• Conducts in-depth literature reviews on medical imaging and drug analysis, evaluates complex machine learning applications, develops hypotheses on data collection, model architecture, and training strategies and assesses feasibility and technical requirements for integrating findings into existing projects.
• Designs and develops machine learning computer models (i.e. algorithms) for medical imaging, bioinformatics and drug development applications.
• Performs analysis of tissue images of cancer and protein-ligand binding affinity using novel machine learning with advanced algorithms such as Alphafold3 for molecule processing and foundation models for image processing.
• Modifies and tunes existing programming modules to integrate with image management platform, enabling the execution of in-house AI models on imaging data.
• Analyses results of machine learning algorithms, documents and prepares reports accordingly.

Consequence of Error/Judgement
Exercises judgment in the design and specifications of new machine learning software and algorithms and makes recommendations for the adoption of specific algorithms.

Supervision Received
Works independently within task objectives. Works within well defined guidelines and procedures, but exercises judgment in establishing priorities and carrying tasks through to completion; new or unusual problems are referred to supervisor.

Supervision Given
May give work assignments to technical staff.

Minimum Qualifications
Undergraduate degree in Engineering or Applied Science. Minimum of one year 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

Ideal candidates should have a solid grasp of:

• ntermediate algorithms and data structures.
• High-level programming languages (Python, JavaScript, etc).
• Knowledgeable with containerization software (Docker, Kubernetes, Singularity).
• Digital pathology experience.
• Basic computer vision and image processing techniques.
• Experience with Agile Development.
• Expertise in cloud software development, particularly with ML applications.
• Familiarity with AWS services.