Senior MLOps Engineer
at Manulife
Toronto, ON M4W 1E5, Canada -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 06 May, 2025 | USD 94220 Annual | 07 Feb, 2025 | N/A | Good communication skills | No | No |
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Description:
THE OPPORTUNITY
Join our Global Advanced Analytics team as a Senior MLOps Engineer, and be a driving force in the future of AI/MLOps! We focus on developing new MLOps architecture, tools, and standards to empower our AI/ML developers by applying AI to deliver it more efficiently. Our goal is to enhance operational efficiency and drive innovation. If you’re passionate about the evolving landscape of LLM and Generative AI, we want to hear from you!
In this pivotal role, you will be responsible for maintaining and enhancing Python libraries, lightweight applications, and CI/CD pipelines. These are crucial for enabling our AI/ML developers to efficiently track experiments, conduct testing, streamline deployment, and monitor model health. You will collaborate with AI/ML project teams to facilitate the adoption of MLOps tools and standards, incorporating feedback to continuously refine our tooling features. Your contributions will ensure the seamless integration of LLM and Generative AI use-cases with existing MLOps practices and infrastructure.
Responsibilities:
- Foundational CI/CD Pipeline Development for AI/ML: Implement reusable CI/CD pipelines to automate testing and deployment processes, focusing on ML experiment management, validation, drift detection, and model retraining.
- Collaboration and Support: Partner with AI/ML project teams across multiple countries to help them adopt MLOps tools and standards, providing guidance and support as needed.
- Collaborator Engagement: Gather feedback from collaborators to improve and enhance MLOps tools and features, ensuring they meet the evolving needs of our teams.
- Establish and implement effective practices and standards for MLOps processes to ensure efficient and streamlined operations.
- Industry Insights: Stay updated with advancements in LLM and Generative AI models, enhancing MLOps capabilities to support LLM Ops needs.
- Cross-Functional Collaboration: Work with data scientists, software engineers, architects, and operations teams to ensure seamless integration and operation of MLOps and LLM Ops solutions.
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Application Programming / Maintenance
Software Engineering
LLM
Proficient
1
Toronto, ON M4W 1E5, Canada