AI Engineer (Agentic Systems)

CanadaRemoteFull-timemid

Machine Learning EngineerData

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Quick Summary

Requirements Summary

Degree in Computer Science, Engineering, or a related technical discipline. Strong Python programming skills and experience building production-grade AI/ML systems.

Technical Tools

Machine Learning EngineerData

Join a high-performing team of engineers and data scientists working at the forefront of artificial intelligence and advanced data technologies. In this role, you will design and build sophisticated agentic systems that solve real-world problems and deliver practical value. You will work across structured and unstructured data, turning cutting-edge research into scalable, production-ready AI solutions. The position offers exposure to challenging projects for organizations ranging from innovative startups to established global businesses. You will collaborate in a fast-paced, intellectually curious environment that values critical thinking, technical excellence, and experimentation. With a strong focus on ownership and impact, you will help shape the next generation of AI-powered products and systems.

Architect, develop, and deploy complex agentic systems, including orchestration, tool use, memory, and state management.
Build production-grade AI and machine learning systems using Python.
Design, train, evaluate, and continuously improve machine learning and deep learning models.
Apply strong foundations in statistics, optimization, and machine learning to solve complex real-world problems.
Develop scalable AI solutions that work with structured and unstructured data.
Establish and improve AI evaluation, observability, reliability, and infrastructure practices.
Translate emerging AI research and techniques into functional prototypes and practical applications.
Apply critical thinking and product judgment to identify opportunities, overcome technical challenges, and deliver effective solutions.

Requirements

~1 min read

Degree in Computer Science, Engineering, or a related technical discipline.
Strong Python programming skills and experience building production-grade AI/ML systems.
Demonstrated experience architecting complex agentic systems, including orchestration, tool integration, memory, and state management.
Strong theoretical and practical knowledge of machine learning, deep learning, statistics, and optimization.
Experience designing, training, evaluating, and improving machine learning models.
Familiarity with AI evaluation, observability, system reliability, and scalable infrastructure.
Ability to rapidly translate cutting-edge research into working prototypes.
Excellent problem-solving skills, strong product instincts, and a proactive, action-oriented mindset.
Nice to have: Knowledge of data privacy, permission-aware AI systems, and secure AI architecture.