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Lead ML Ops Engineer

RBC

Toronto

On-site

CAD 100,000 - 130,000

Full time

29 days ago

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Job summary

A leading financial institution in Toronto is seeking a Lead ML Ops Engineer to build and manage CI/CD for ML on OpenShift using cutting-edge technologies. You will collaborate with teams to deploy and manage LLMs while ensuring the integration of models into data pipelines. A strong background in MLOps and Python is essential, along with a Bachelor's degree in a related field. This role offers compelling opportunities within a high-performing team, alongside competitive salary and comprehensive rewards program.

Benefits

Comprehensive Total Rewards Program
Competitive compensation
Career development opportunities

Qualifications

  • 3+ years of hands-on experience in MLOps/LLMOps.
  • Production experience with LLMs and agentic AI.
  • Excellent communication and cross-team leadership skills.

Responsibilities

  • Build and operate CI/CD for ML and GenAI on OpenShift using GitHub Actions.
  • Deploy and manage LLMs and agentic services on cloud.
  • Collaborate with data scientists and engineers to integrate models into microservices.

Skills

MLOps
Python
SQL
GitHub Actions
Airflow

Education

Bachelor's degree in Computer Science or Engineering

Tools

Kubernetes
OpenShift
AWS
Azure
Job description
What is the opportunity?

Join GFT as a Lead ML Ops Engineer to build and manage CI/CD for ML and agentic AI on OpenShift using GitHub Actions and Airflow. You will partner with machine learning engineers and data engineers to deliver business value with agile practices, maintaining data governance and security. Design scalable pipelines, support data ingestion and feature engineering, and integrate models into APIs and services. Participate in architecture reviews and approvals, set operational standards, and maintain documentation. Own monitoring and incident triage/resolution, optimizing reliability, performance, and cost while enabling teams to safely ship GenAI solutions.

What will you do?
  • Build and operate CI/CD for ML and GenAI on OpenShift using GitHub Actions and Airflow.
  • Deploy, scale, and manage LLMs and agentic services on OCP and cloud (AWS/Azure).
  • Architect and deliver solutions/PoCs for cutting‑edge GenAI (RAG, tool‑use, agent orchestration).
  • Own model lifecycle ops: versioning, registries, feature stores, vector DBs, and GPU environments.
  • Build and maintain Model Context Protocol (MCP) integrations (servers/clients and tool adapters) to let LLM agents securely invoke internal APIs, data sources, and actions on OpenShift.
  • Define release/rollback procedures; ensure reliable maintenance of deployed models.
  • Collaborate with data scientists, ML engineers, and data engineers to integrate models/APIs into microservices and data pipelines.
  • Drive platform roadmap, standards, and documentation; enable teams via tooling, templates, and best practices.
What do you need to succeed?
Must Have
  • Hands‑on MLOps/LLMOps with containers/Kubernetes/OpenShift; CI/CD via GitHub Actions; orchestration with Airflow (good‑to‑have).
  • Production experience with LLMs and agentic AI: RAG, vector search, prompt management, and serving patterns.
  • Hands‑on with agentic AI and Understanding of MCP: design agent tool‑use flows, deploying MCP servers/tools.
  • Expert in Python and SQL. Cloud experience (AWS or Azure); designing scalable and secure architectures along with the data architecture team and ML Engineers.
  • 3+ years hands on experience.
  • Proven production experience running ML/GenAI with monitoring and performance tuning.
  • Excellent communication and cross‑team leadership; BS in CS/Engineering or related (MS/PhD preferred).
  • Being able to articulate technical concepts to leadership or key stakeholders.
  • Foster and drive key innovations within the extended team with emerging technology.
Nice to Have
  • Experience working with Snowflake and SageMaker; model registries/feature stores (MLflow, Feast).
  • Guardrails/safety, evaluation methods, and cost optimization for GPU/LLM workloads.
  • Understanding of MCP (capability schemas, resources/tools, session management) and telemetry for tool calls (latency/success/cost).
  • LLM frameworks and evaluation/guardrails.
What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
  • Leaders who support your development through coaching and managing opportunities.
  • Ability to make a difference and lasting impact.
  • Work in a dynamic, collaborative, progressive, and high‑performing team.
  • A world‑class training program in financial services.
  • Opportunities to do challenging work.
  • Opportunities to take on progressively greater accountabilities.
  • Opportunities to building close relationships with clients.
  • Access to a variety of job opportunities across business and geographies.
Note

Applications will be accepted until 11:59 PM on the day prior to the application deadline date above.

Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages

Additional Job Details

Address: RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-01-07

Application Deadline: 2026-01-18

Inclusion and Equal Opportunity Employment

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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