ML Engineer – Generative AI & LLMs (Remote)
At a glance
Mid-level Machine Learning Engineering role at Ample Insight Inc. Remote, Canada · contract.
Pay not stated ML Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Design, test and turn scalable machine-learning solutions into working products with clients and teammates
- Build LLM systems using real-world data, then move promising prototypes into production services
- Develop quick prototypes from new tools and research ideas, with a focus on production readiness
- Apply statistics and machine learning to address client problems and product or business outcomes
What you bring
- You have strong LLM engineering skills and know how to work with major providers and their recommended practices
- You can move from fast experiments to production services and have hands-on statistics and machine-learning experience
- You work with Python ML libraries and development tools such as Git, Docker, SQL, Bash and FastAPI
- You hold at least a bachelor's degree in computer science or a related engineering discipline involving coding
Who this fits
This mid-level contractor role suits an engineer who enjoys open-ended client work and can explain their ownership of LLM projects. The role is remote and based in Toronto.
From the employer
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.
- 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.