This is a 8 months’ Full-time. Co-op employment opportunity starting Jan 2026.
This position is open for Burnaby office. To apply, please fill out the application form and include a copy of your transcript in your application.
Please note: Application without a transcript will NOT be considered.

QUALIFICATIONS

• Second year or higher BS or MS in Computer Science, Engineering or equivalent
• Experience with Python a must
• Experience using the Linux development environment
• Hands-on experience using OpenAI API, Anthropic API, tools including advanced open source AI models
• Demonstration of initiative in the implementation of generative AI tools
• Development of presentations that teach others interesting topics
• An aptitude for working in uncertainty, pathfinding and exploring a new space
• an understanding of neural network model testing and training
• An understanding of generative AI models, their strengths and weaknesses
• Experience in implementing front-end and back-end web implementations
• Familiarity and experience with git

HIGHLY DESIRABLE SKILLS

• Experience implementing and training neural network designs
• Familiar with generative AI programming infrastructure such as Cursor and Claude Code
• Deep understanding of the structure of generative AI models
  We thank you for your interest, however, only candidates selected for an interview will be contacted.

ACKNOWLEDGMENT AND AGREEMENT

NETINT Technologies Inc. is an equal opportunity employer and strives to ensure that its hiring process meets the needs of all persons with disabilities. As such, NETINT will provide reasonable accommodation for any applicant, as requested during the hiring process

• Develop Python functions to consolidate internal data sources
• Use OpenAI, Anthropic and Openrouter API to link internal models
• Use open source AI libraries to enhance internal productivity
• Develop tools that support generative AI development using generative programming tools like Claude Code and Cursor
• Develop infrastructure to test and train state of the art learned compression models
• Develop internal training presentation on tool and model usage
• Work with senior engineers to understand their core needs and implement tools to improve efficiency