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ML Engineer – Generative AI & LLMs (Remote)
Toronto, ON, Canada
Live, first seen by us 4 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Contract — employment source
Employment type in the employer’s posting: Contract
From the employer’s posting
What you’ll work on
Full postingDesign, prototype, and productize scalable machine learning solutions
Build systems with LLMs and real-world data
Work with clients and teammates on open-ended problems
From the employer’s posting
design, prototype, and productize scalable machine learning solutions
building cutting-edge systems with LLMs and real-world data
work closely with clients and teammates
What you’ll bring
All qualificationsCore experience
- Expertise in LLM engineering and popular LLM providers
- Turning prototypes into production-ready services
- Hands-on statistics and machine learning experience
- Python ML stack (Pandas, NumPy, scikit-learn, XGBoost, PyTorch)
- Bachelor's degree or higher in computer science or a coding-related engineering field
Qualification wording
Expertise in LLM engineering, including familiarity with popular LLM providers and their best practices
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.
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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 31, 20264 days ago
- Recorded sightings
- 5
- Last seen by us
- Nov 4, 2026
- Reposted
- once since May 14, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
Ample Insight is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- 50% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Bash
- Python
- SQL
- AWS
- Azure
- Docker
- Neo4j
- Spark
- FastAPI
- NumPy
- pandas
- PyTorch
- scikit-learn
- XGBoost
Where the posting names them
- 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
Your next step
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Has Ample Insight posted this job before?
Yes. We’ve followed one other ML Engineer – Generative AI & LLMs (Remote) job there since May 2026. It came down after 169 days.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
Source details
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.