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
remoteroles summary, based on the employer's posting.
What you'll do
- Design and test machine learning solutions with clients and teammates, then turn them into usable products
- Build LLM-based systems that work with real-world data and can scale
- Quickly test new tools and research ideas, then make successful prototypes production-ready
- Use statistical and machine learning methods to address data problems and product or business outcomes
What you bring
- You have strong LLM engineering skills, including knowledge of major providers and their recommended practices
- You can move from rapid experiments to production services, with hands-on statistics and machine learning experience
- You work comfortably 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 coding-focused engineering discipline
Who this fits
This contractor role suits a mid-level machine learning engineer who enjoys open-ended client work and rapid prototyping. It 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.
Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Machine Learning EngineeringRemote
Find me workBy the team behind remoteroles.