Senior ML Engineer

Toronto, ON
Hybrid
Posted Oct 21, 2026
1 position

$90–$100 / hour

Opens LinkedIn

Employment type: Contract
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Office presence: 1 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design, build, optimise, and deploy scalable production machine learning and Generative AI solutions, including personalisation and recommendation systems. Collaborate with engineering, data, and product teams to take solutions from development to production, using GCP technologies and containerisation tools.

Job details

Senior Machine Learning Engineer – GenAI & Personalisation Location: Toronto, ON Work Model: Hybrid – 1 day onsite per week Contract: 6 months, with a chance of extension Rate: Up to $100/hour INC We’re looking for a Senior Machine Learning Engineer to join a large enterprise organisation working on next-generation personalisation, recommendation systems and Generative AI initiatives. This is a hands-on engineering role focused on building and deploying production-grade ML solutions at scale. What You’ll Be Doing Design, build and deploy scalable machine learning and GenAI solutions in production. Contribute to the development of personalisation and recommendation systems, including multimodal use cases. Build and optimise ML solutions using Python and SQL. Work with GCP technologies, including Vertex AI, BigQuery, BigTable, AlloyDB and Cloud Composer. Develop GenAI applications and workflows using technologies such as LangChain and LangGraph. Containerise and deploy applications using Docker and Kubernetes. Work closely with engineering, data and product teams to take ML solutions from development through to production. What We’re Looking For Strong professional experience in Machine Learning Engineering with hands-on production deployment experience. Advanced Python and SQL skills. Strong experience with Google Cloud Platform (GCP) and cloud-based ML/data environments. Hands-on experience with Vertex AI and modern GCP data technologies. Experience developing Generative AI / LLM-based solutions. Experience with LangChain and/or LangGraph. Strong understanding of recommendation systems, personalisation or similar ML use cases. Experience with Docker and Kubernetes. Proven experience building scalable, production-grade ML systems, rather than purely research or proof-of-concept work. Nice to Have Experience working with multimodal AI models. Experience building large-scale recommendation engines. Experience working within complex, enterprise-scale technology environments. This is a strong opportunity for a senior ML engineer who enjoys staying hands-on and wants to work on production-scale GenAI, personalisation and recommendation technology. This posting is for an existing vacancy with the organization. AI may be used to screen, assess or select applicants for the position.

What you’ll do

Requirements

Candidates should have strong professional machine learning engineering experience, including hands-on deployment of scalable, production-grade systems, and advanced Python and SQL skills. They should also have experience with GCP and Vertex AI, Generative AI or LLM solutions, LangChain or LangGraph, recommendation or personalisation use cases, Docker, and Kubernetes.