Posted last month
Lead, AI/Machine Learning Engineer
@ Urban Ridge Supplies
Toronto, Ontario
Overview
OMERS is hiring a Lead, AI/Machine Learning Engineer to join the AI Delivery and Innovation team, building and shipping AI and Generative AI solutions across investments, pension services, finance and corporate functions. The role is hands-on from prototyping through production deployment, including LLM applications, RAG pipelines, MLOps/LLMOps and mentoring. The posting states a salary of $86,000 to $130,000 per year, full-time, with a hybrid guideline of 4 days per week in the office.
Pay:
$86,000–$130,000 a year
Responsibilities:
- Design and build end-to-end AI/ML and GenAI solutions, including LLM apps and RAG pipelines
- Build and maintain MLOps/LLMOps pipelines and monitoring
- Deliver AI solutions on Azure AI Foundry and Copilot Studio
- Mentor engineers and contribute to reusable component libraries
Requirements summary:
- 3+ years software engineering, 2+ years production AI/ML or GenAI
- Hands-on experience with LLMs, RAG and fine-tuning
- Experience with LangChain, LlamaIndex or Semantic Kernel
- Strong SQL and experience with Databricks or Snowflake
- Excellent communication with non-technical stakeholders
Tools & skills
Benefits mentioned
Source and dates
Employer career site / ATS feed · teamtailor
- Employer posting date
- 2026-09-24
- First seen by our source
- 2026-10-11
- Source record updated
- 2026-10-30
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Lead |
| Department | Data & analytics |
| Experience | 3+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (preferred) |
| Fields of study | Computer Science, Engineering, Mathematics |
| Perks mentioned | Retirement plan, Performance bonus |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Urban Ridge Supplies
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Supplying high-quality pipes for residential, commercial, and industrial needs.
Full company description
Supplying high-quality pipes for residential, commercial, and industrial needs across Karachi. Fast delivery. Trusted quality.
- LinkedIn followers
- 14,005
- Reported office locations
- Sheikh Mohammed bin Rashid Boulevard 1, Zabeel, Dubai, AE
- Other recorded names
- Urban Ridge Supplies
- Profile identifies a recruitment agency
- No
Supplying high-quality pipes for residential, commercial, and industrial needs across Karachi. Fast delivery. Trusted quality.
| Field | Value |
|---|---|
| Industry | Wholesale Building Materials |
| Company size | 2-10 employees |
| Headquarters | Zabeel, Dubai |
| Organization type | Privately Held |
| Open jobs on Jobsy | 124 |
| View page |
Choose a workplace that empowers your impact.
Join a global workplace where employees thrive. One that embraces diversity of thought, expertise and experience. A place where you can personalize your employee journey to be — and deliver — your best.
We are a purpose-driven, dynamic and sustainable pension plan. An industry leading global investor with teams in Toronto to London, New York, Singapore, Sydney and other major cities across North America and Europe. We embody the values of our 665,000 members, placing their best interests at the heart of everything we do.
Join us to accelerate your growth & development, prioritize wellness, build connections, and support the communities where we live and work.
Don’t just work anywhere — come build tomorrow together with us.
Know someone at OMERS or Oxford Properties? Great! If you're referred, have them submit your name through Workday first. Then, watch for a unique link in your email to apply.
The Lead, AI/Machine Learning Engineer will join the AI Delivery and Innovation team within the Platform Engineering, AI and Advanced Analytics department. This team acts as a central hub for AI capability at OMERS, partnering with Software Engineering, Customer Success and Innovation (CSI), and business areas to prototype, build, and ship AI solutions across Investments, Pension Services, Finance, and Corporate functions.
Reporting to the Associate Director, AI and ML, this role is hands-on across the full AI delivery lifecycle — from rapid prototyping and proof-of-concept development through to production-ready deployment. You will design and implement AI/ML and Generative AI solutions, operationalize them through robust engineering practices, and help shape how OMERS leverages AI to deliver measurable business outcomes. This is an opportunity to work at the intersection of cutting-edge AI, modern engineering, and real-world business problems in a collaborative, fast-paced environment.
You Will Be Responsible For
- Designing and building end-to-end AI/ML and Generative AI solutions, including LLM applications, RAG pipelines, agentic workflows, and traditional ML models.
- Building and maintaining MLOps/LLMOps/GenAIOps pipelines, including experiment tracking, model and prompt versioning, CI/CD, observability, drift detection, and automated retraining.
- Building AI solutions using enterprise platforms, including Azure AI Foundry, Copilot Studio, and other approved AI platforms.
- Working with vector databases, embeddings, and retrieval systems to ground LLMs on OMERS enterprise knowledge.
- Conducting applied research on emerging models, agent frameworks, and AI engineering patterns, and translating findings into practical solutions and reusable components.
- Collaborating with Software Engineering, Customer Success, and business stakeholders in an Agile environment to move initiatives from prototype to production and ensure successful adoption.
- Contributing to AI governance, responsible AI practices, and architecture standards; embedding responsible AI principles and controls in everything you build.
- Mentoring and coaching teammates through pairing, code reviews, and knowledge sharing; contributing to reusable skill, sub-agent, and component libraries to accelerate delivery.
- Identifying, defining, and implementing improvements to existing engineering practices, tooling, and delivery processes while managing multiple initiatives and ensuring timely delivery.
- 3+ years of professional software engineering experience, including 2+ years building and deploying production AI/ML or Generative AI solutions.
- Hands-on experience with LLMs, including OpenAI, Anthropic, and open-source models; prompt engineering; RAG architectures; and fine-tuning.
- Practical experience with one or more LLM/GenAI frameworks, such as LangChain, LlamaIndex, or Semantic Kernel.
- Strong foundation in machine learning, including classical ML, such as scikit-learn, and deep learning, such as PyTorch or TensorFlow, with experience in feature engineering, model evaluation, and experimentation.
- Experience implementing MLOps/LLMOps capabilities, including MLflow, Kubeflow, or equivalents; model registries; CI/CD for ML; observability, such as Arize, Langfuse, or similar; and drift monitoring.
- Proven ability to design, build, and maintain production-grade services and full-stack applications that integrate AI capabilities.
- Solid experience with cloud platforms, particularly Azure, including Azure AI Foundry and Azure OpenAI; working knowledge of GCP and Vertex AI is an asset.
- Strong SQL skills and experience working with modern data platforms, including Databricks and Snowflake, and vector databases, including Azure AI Search, Pinecone, pgvector, or similar.
- Demonstrated success delivering complex technical projects end-to-end, aligning expectations with various partners, and navigating ambiguity from prototype to production.
- Strong software engineering practices, including Git, code reviews, automated testing, and CI/CD, with a bias toward shipping reliable, maintainable software.
- Excellent communication skills, with the ability to explain technical concepts and trade-offs clearly to non-technical stakeholders and senior management.
- Motivated to work in a collaborative environment with fast feedback, shared ownership of outcomes, and a focus on team success.
- Experience with agent frameworks, such as Microsoft Agent Framework or Google ADK, and agentic workflows.
- Experience containerizing workloads, including Docker and Container Applications, and deploying across cloud and on-premises GPU infrastructure.
- Exposure to AI/ML observability and evaluation tooling beyond the core stack, and experience designing evaluation harnesses and guardrails for LLM-based applications.
- Familiarity with responsible AI principles, governance frameworks, and enterprise architecture standards.
- Experience in financial services, pensions, asset management, or related domains.
- Bachelor’s Degree in Computer Science, Engineering, Mathematics, or a related quantitative field; Master’s degree is an asset, or equivalent work experience.
- Experience mentoring engineers and contributing to communities of practice or reusable component libraries.
This posting is for an existing vacancy.
The expected salary range for this position is $86,000.00 - $130,000.00 per year.
You may also be eligible to receive an annual Incentive Award pursuant to our Short-term Incentive plan and our Long-Term Incentive plan (if applicable), and to participate in our group benefits and retirement plans – details on these elements of compensation are included within OMERS & Oxford offer letters.
As one of Canada’s largest defined benefit pension plans, our people-first culture is at its best when our workforce reflects the communities where we live and work — and the members we proudly serve.
From hire to retire, we are an equal opportunity employer committed to an inclusive, barrier-free recruitment and selection process that extends all the way through your employee experience. This sense of belonging and connection is cultivated up, down and across our global organization thanks to our vast network of Employee Resource Groups with executive leader sponsorship, our Purpose@Work committee and employee recognition programs.
Artificial intelligence (AI) tools are used to support certain stages of the OMERS recruitment process. While AI assists us in our process, human judgment and decision-making remain central to our candidate experience.
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