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Job summary
A fast-growing consulting firm in Toronto is seeking a Machine Learning Engineer to design and productize scalable solutions with LLMs. You will work within a high-performing team focusing on rapid prototyping and collaboration with clients. Ideal candidates will have expertise in LLM engineering and experience with the Python ML stack.
Benefits
Qualifications
- Expertise in LLM engineering with experience in agentic systems is a strong plus.
- Ability to rapidly prototype tools and turn them into production-ready services.
- Hands-on experience with statistics, machine learning, and Python ML stack.
Responsibilities
- Design, prototype, and productize scalable machine learning solutions.
- Collaborate closely with clients to develop production-ready services.
- Contribute to a high-performing team emphasizing pragmatic execution.
Skills
Education
Tools
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.
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.
- Design, prototype, and productize scalable machine learning solutions using LLMs and real-world data.
- Collaborate with clients and teammates to turn ideas into production-ready services.
- Contribute to a fast-paced, high-performing team that emphasizes clear thinking and pragmatic execution.
- 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.
- We have competitive compensation.
- We believe in accountability and NOT micro-management.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.
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