Key Facts

Remote From:

Canada

Full time

English

Hard Skills

Other Skills

•
Accountability
•
Adaptability
•
Teamwork
•
Critical Thinking
•
Analytical Thinking
•
Business Acumen

Roles & Responsibilities

Expertise in LLM engineering with familiarity of popular LLM providers and best practices.
Experience building or working with agentic systems (tool use, memory, planning, multi-agent coordination) and ownership of LLM projects.
Strong prototyping ability with a track record of turning prototypes into production-ready ML services; hands-on statistics and machine learning; proficient in Python ML stack (Pandas, NumPy, scikit-learn, XGBoost, PyTorch).
Proficiency with development tools (Git, Docker, SQL, Bash, FastAPI) and a Bachelor's degree or higher in Computer Science or related engineering field; bonus familiarity with AWS/Azure, GitHub Actions, Spark, Neo4j Cypher, and graph databases.

Requirements:

Design, prototype, and productize scalable ML solutions using LLMs and real-world data in collaboration with clients and internal teams.
Turn prototypes into production-ready services with reliable, scalable deployments.
Tackle open-ended problems in a fast-paced environment while maintaining high standards of quality and impact.
Own LLM projects from ideation to delivery, including clear documentation and stakeholder communication.

Job description

Company Description

You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.

Job Description

We’re looking for Machine Learning Engineers who are passionate about building cutting-edge systems with LLMs and real-world data. In this role, you’ll work closely with clients and teammates to design, prototype, and productize scalable machine learning solutions.

You’ll be part of a collaborative, high-performing team that values clear thinking, pragmatic execution, and continuous learning. If you thrive in fast-paced environments, enjoy tackling open-ended problems, and care deeply about the quality and impact of your work, we’d love to connect.

Qualifications

Must have: Expertise in LLM engineering, including familiarity with popular LLM providers and their best practices. Experience building or working with agentic systems (e.g. tool use, memory, planning, multi-agent coordination) is a strong plus. Show us your LLM projects and detail your ownership and contributions.
Strong ability to rapidly prototype cutting-edge tools and research ideas, with a track record of turning prototypes into production-ready services.
Hands-on experience with statistics and machine learning. Comfortable working with the Python ML stack: Pandas, Numpy, scikit-learn, XGBoost, PyTorch, etc. Proficient with development tools such as Git, Docker, SQL, Bash, and FastAPI.
Strong analytical mindset and business acumen; able to think critically about data and its impact on product or business outcomes.
Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding.
Bonus: Familiarity with AWS or Azure, GitHub Actions, Spark, Neo4j Cypher, and graph databases.