AI Jobs in Canada

View detail

Contributors design original computational statistics problems simulating real mathematical research workflows, create problems requiring Python programming (using Numpy, SciPy, Sympy), ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly with verified correct answers.

View detail

Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.

View detail

Design and build abstractions and platform-level systems that improve all of Harvey’s agentic products; own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context; build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively; partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products; evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.

View detail

The Senior Full Stack Software Engineer is responsible for owning technical delivery end-to-end, shaping the architecture of ML-powered applications, and leading implementation across cloud services, APIs, and modern front-end frameworks with Claude Code, the Claude Agent SDK, and the Claude API integrated into design, building, and shipping processes. They act as the technical backbone of their project pod, balancing hands-on development with technical leadership, architectural decision-making, and client-facing collaboration. Responsibilities include reducing project risk through proactive ownership of epic-level design and execution, improving technical decision-making via research and evaluation of solutions including AI tooling, increasing client confidence by leading technical discovery sessions and acting as a technical SME, leading feature and epic-level implementation, leading architecture and solution design for moderately complex solutions, championing AI engineering best practices within the pod, providing mentorship and technical leadership including code review and hiring assistance, engaging with clients for technical discovery and scoping, and implementing higher-level testing and quality strategies for deployed solutions and LLM-powered features.

View detail

Collaborate with senior developers to design, build, and test software solutions for the agricultural sector. Contribute to coding, debugging, and documenting software applications. Assist in the development of new features from concept to deployment. Assist in research and development to improve the AI powered Assistant. Help optimize and improve the performance of existing software systems. Participate in code reviews and contribute to development process improvements and best practices. Test software functionality and troubleshoot issues. Collaborate with cross-functional teams such as product managers and data scientists to align technical solutions with business objectives. Stay updated with trends and technologies in software development and agriculture.

View detail

Testing of AI based conversational products; Monitoring and improving quality assurance process ensuring any agreed-upon standards and procedures are followed; Providing a high level of data quality awareness across multiple teams; Evaluating and identifying where enhancements in accuracy of models are required; Detailed testing feedback preparation to help the team to improve AI models.

View detail

Craft, optimize, evaluate, and benchmark prompts to enhance AI performance. Design and refine client-specific prompts ensuring accuracy and relevance. Define tool descriptions for agentic frameworks to improve AI interactions. Improve prompts for clarity and performance, automate testing with scripts, and evaluate large language models (LLMs) to identify best-fit solutions. Develop evaluation frameworks and benchmark prompts to establish best practices. Collaborate with Customer Success and Data Science teams while maintaining clear documentation on prompt development and optimization. Stay current with advancements in natural language processing (NLP), experiment with new prompting strategies, and refine model-specific adaptations.

View detail

Contributors may design original computational chemistry problems that simulate real chemistry research workflows; create problems requiring Python programming to solve using numpy, scipy, and chemical libraries; ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes; develop problems requiring non-trivial reasoning chains in physical chemistry, quantum chemistry, and molecular modeling; base problems on real research challenges or practical applications from chemistry practice; verify solutions using Python with standard computational chemistry approaches; and document problem statements clearly and provide verified correct answers.

View detail

Contributors may design original computational mathematics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve (using Numpy, SciPy, Sympy), ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks), develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly while providing verified correct answers.

View detail

As the Manager for the Sovereign AI Modelling team, you will manage a team of scientists and engineers, fostering a culture of high-performance, innovation, and continuous learning. You will stay up-to-date with the latest research in large language models (LLMs) and related fields, lead scalable strategies to train frontier models, and collaborate with cross-functional teams across modelling, forward-deployed engineering, and solutions architecture. The role is hands-on and research-driven, involving designing and implementing novel research ideas, shipping state-of-the-art models to production, and maintaining deep connections to academia and government. You will dive into the latest literature on LLMs, experiment with frontier models, and lead a team of talented engineers and researchers to build scalable, production-ready solutions.