Date Posted: 08/31/2026
Req ID: 50037
Faculty/Division: VP - Research
Department: SciNet
Campus: St. George (Downtown Toronto)
Position Number:
Existing Vacancy: Yes

Description:

Your opportunity:

SciNet is in the process of installing a new AI capability, with a large number of high performance GPUs, as part of the ISED Sovereign AI Compute initiative. The incumbent is expected to support the platform and assist users in AI applications research, and in AI-assisted research in general. Under general direction of the CTO, the Scientific Applications Analyst & AI Analyst provides senior IT services and training in GPU programming, data science applications, and scientific computing workflows for the SciNet advanced computing consortium. The incumbent supports users in designing, training, and validating machine learning models and deep learning algorithms; analyzing large datasets, perform data cleaning, transformation, and feature engineering to prepare data for model training; deploying AI solutions into production environments, ensure they integrate seamlessly with existing software applications and infrastructure and monitoring the performance of AI systems and make adjustments to improve efficiency, accuracy and scalability. Additionally, the incumbent will assist users (clients) in deployment of AI strategies for AI-assisted scientific research.

Your responsibilities will include:

• Analyzing, recommending, and designing highly complex software architecture
• Developing and updating architectural framework for highly complex and confidential university-wide applications
• Writing complex technical code
• Analyzing and making recommendations for programming enhancements
• Evaluating programming code to ensure it has validity, compatibility, and that it meets appropriate standards
• Providing formal job-related training
• Building and strengthening relationships with stakeholders and partners of strategic importance
• Acting as an expert resource to developers on architecture, technical standards and coding techniques

Essential Qualifications:

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or quantitative sciences; or acceptable combination of equivalent experience.
• Minimum eight years' experience with advanced computing scientific applications or large-scale, data- driven scientific computations.
• Significant experience and understanding of scientific numerical codes, compilers, code optimization, file input/output strategies, and data management.
• Experience using data analysis and machine learning libraries.
• Excellent knowledge of computing hardware and networking.
• Solid knowledge of Fortran, C,C++ under Linux/Unix, and a scripting language like R and Python.
• Demonstrated abilityto program efficiently on serial, vector and parallel systems, with the ability analyze and improve software codes and interface well with researchers across all disciplines on their computing needs.
• Excellent verbal and written communication skills with the ability to communicate highly technical terms and concepts to people of non-IT background.

Assets (Nonessential):

• Visualization expertise and presentation/training skills an asset.

To be successful in this role you will be:

• Goal oriented
• Motivated self-learner
• Proactive
• Problem solver
• Self-directed

Closing Date: 09/10/2026, 11:59PM ET
Employee Group: USW
Appointment Type: Grant - Term This is a two (2) year Term role, with the possibility of renewal.
Schedule: Full-Time
Pay Scale Group & Hiring Zone:
USW Pay Band 18 -- $116,547. with an annual step progression to a maximum of $149,043. Pay scale and job class assignment is subject to determination pursuant to the Job Evaluation/Pay Equity Maintenance Protocol.
Job Category: Information Technology (IT)
Recruiter: Anita Chooraman

Job descriptions are available upon request for internal applicants.