Scientific Programmer & AI Analyst
Job Description
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, Hardware and Operations, the Scientific Programmer Analyst & AI Analyst provides senior IT services, particularly with GPU infrastructure, networking and storage for the SciNet advanced computing consortium. The incumbent is involved 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.
Your responsibilities will include:
- Developing and updating architectural framework for highly complex and confidential university-wide IT systems
- Developing, maintaining, and ensuring the security of University networks
- Analyzing, troubleshooting and testing highly complex systems
- Analyzing operational requirements to implement plans for network and internet presence
- Configuring system applications according to needs
- Devising solutions to operational problems within the capacity and operational limitations of installed equipment
- Defining requirements and scope of complex projects with broad impact and long-term consequences
- Serving as an expert resource to a group of professionals in the speciality
Essential Qualifications:
- Bachelor’s Degree in Computer Science, Information Technology, Engineering, or quantitative sciences; or acceptable combination of equivalent experience
- Six to seven (6-7) years’ relevant experience with high performance computation for scientific applications.
- Significant experience and understanding of scientific numerical codes, compilers, code optimization, data science, and the Linux kernel & OS.
- Extensive knowledge of computing hardware and networking.
- Strong knowledge of modern programming languages under Linux/Unix
- Strong knowledge of cyber-security technologies.
- Ability to learn on the job in a fast-paced environment
- Ability to handle several tasks, and effectively prioritize and meet deadlines
- Excellent verbal and written communication skills with the ability to communicate highly technical terms and concepts to people of non-technical background.
Assets (Nonessential):
- Visualization skills and background an asset.
To be successful in this role you will be:
- Goal oriented
- Motivated self-learner
- Proactive
- Problem solver
- Team player