ML Engineer – Generative AI & LLMs

Toronto, ONHybridContractPosted 1 month agoHidden Gem · Himalayas

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Required skills

LLM engineering
LLM projects
agentic systems
tool use
memory
planning
multi-agent coordination
Python ML stack
Pandas
Numpy

Nice to have

AWS
Azure
GitHub Actions
Spark
Neo4j Cypher
graph databases

Role summary

We are seeking Machine Learning Engineers with expertise in Generative AI and LLMs to design, prototype, and productize scalable ML solutions. The role involves working with LLM providers, agentic systems, and the Python ML stack (Pandas, Numpy, scikit-learn, XGBoost, PyTorch). Proficiency in development tools like Git, Docker, SQL, Bash, and FastAPI is required. Familiarity with cloud platforms (AWS, Azure) and data engineering tools (Spark, Neo4j) is a plus. The position emphasizes analytical thinking, business acumen, and the ability to translate research into production-ready services within a fast-growing consulting firm based in Toronto.

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.

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.

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.

Originally posted on Himalayas

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