ML Engineer – Generative AI & LLMs (Remote)
Toronto, ON, Canada
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingIn this role, you’ll work closely with clients and teammates to design, prototype, and productize scalable machine learning solutions.
From the employer’s posting
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.
What you’ll bring
All qualificationsCore experience
- Experience building or working with agentic systems (e.g.
- 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.
- Proficient with development tools such as Git, Docker, SQL, Bash, and FastAPI.
- Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding.
Qualification wording
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.
Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding.
Education & alternatives
- 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.
Tools in this posting
- Bash
- Python
- SQL
- AWS
- Azure
- Docker
- Neo4j
- Spark
- NumPy
- pandas
- PyTorch
- Xgboost
- scikit-learn
- Fastapi
Source — Tool mentions in context
- 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. Additional Information
Job description
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.
Additional Information
We have competitive compensation.
We believe in accountability and NOT micro-management.
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Toronto, ON, Canada
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- May 14, 2026
- Recorded sightings
- 129
- Last seen by us
- Oct 7, 2026
- Employer says posted
- Feb 12, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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