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Technical Lead -ML Ops / AI Platform

  • Toronto, ON, Canada

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Original job description

Iris's direct client, one of the Top 5 Bank in Canada, is looking to hire a Project Lead - ML Ops / AI Platform for a long-term opportunity.

Our client is a Canadian multinational financial services company and the largest bank in Canada by market capitalization. The bank serves over 17 million clients and has more than 89,000 employees worldwide. Bank is serving individual consumers, small and middle market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk-management products and services.

Project Lead | ML Ops / AI Platform

Location: Toronto, ON (Hybrid – 2-3 Days in Office/week)

Duration: Long-Term Open-Ended Contract

Required Skills & Experience

  • Proven experience in end-to-end lifecycle of ML Ops /GenAI platform build out in cloud (AWS preferred).
  • Has several years of experience in technical product management or cloud platform product leadership.
  • Has hands on experience with cloud infrastructure.
  • AWS Preferred. Strong working knowledge of AWS services such as SageMaker and related services such as ECS, IAM, Cloud Watch, S3 etc.
  • Nice to have familiarity with Infra-as-code such as AWS CDK.
  • Proficient in Github workflows, CI CD, and version control practices.
  • Proficient in Python and its ecosystem of tooling such as Jupyter Notebooks, Packaging, Documentation.

Key Responsibilities

  • Strong blend of technical depth, system design and leadership and management skills and apply these principles to building out an evolving ML / AI platform on cloud.
  • Oversee the design, implementation, and maintenance of ML Ops solution using AWS services like Amazon SageMaker and other platforms.
  • Own relationship with key internal stakeholder management / drive product roadmap - Ensure seamless collaboration across cross-functional teams including data scientists, data engineers, software developers, and business stakeholders, adapting communication for various personas across LoBs.
  • Influence and collaborate with various stakeholders including platform users, architects, cloud engineering, DevOps and others.
  • Lead and manage a geographically distributed team (offshore) of talented engineers, provide technical directions, coach junior members, and manage priorities.

About Iris Software Inc.

With 4,000+ associates and offices in India, U.S.A. and Canada, Iris Software delivers technology services and solutions that help clients complete fast, far-reaching digital transformations and achieve their business goals. A strategic partner to Fortune 500 and other top companies in financial services and many other industries, Iris provides a value-driven approach - a unique blend of highly-skilled specialists, software engineering expertise, cutting-edge technology, and flexible engagement models. High customer satisfaction has translated into long-standing relationships and preferred-partner status with many of our clients, who rely on our 30+ years of technical and domain expertise to future-proof their enterprises. Associates of Iris work on mission-critical applications supported by a workplace culture that has won numerous awards in the last few years, including Certified Great Place to Work in India; Top 25 GPW in IT & IT-BPM; Ambition Box Best Place to Work, #3 in IT/ITES; and Top Workplace NJ-USA.

More about this job

Responsibilities

Lead the design, implementation, and ongoing maintenance of a cloud-based ML/AI platform, using AWS services such as Amazon SageMaker. Own stakeholder relationships and the product roadmap, coordinate cross-functional teams, and lead a geographically distributed engineering team through technical direction, coaching, and priority management.

Requirements

Requires several years of technical product management or cloud platform leadership experience, hands-on cloud infrastructure experience, and proven experience building an end-to-end MLOps or generative AI platform, preferably on AWS. Candidates should be proficient in Python, GitHub workflows, CI/CD, and version control, with working knowledge of AWS services such as SageMaker, ECS, IAM, CloudWatch, and S3; AWS CDK familiarity is an asset.

Skills

  • MLOps
  • Generative AI Platforms
  • AWS
  • Amazon SageMaker
  • Cloud Infrastructure
  • Technical Product Management
  • ECS
  • IAM
  • CloudWatch
  • Amazon S3
  • Infrastructure as Code
  • AWS CDK
  • GitHub Workflows
  • CI/CD
  • Python
  • Team Leadership

Visa sponsorship

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Categories

  • Technology
  • Software
  • Data & Analytics
  • Management & Leadership
  • Finance & Accounting

Keywords

  • MLOps
  • Generative AI
  • AI Platform
  • AWS
  • Amazon SageMaker
  • ECS
  • IAM
  • CloudWatch
  • Amazon S3
  • AWS CDK
  • Infrastructure as Code
  • GitHub Workflows
  • CI/CD
  • Version Control
  • Python
  • Jupyter Notebooks
  • Cloud Infrastructure
  • Technical Product Management
  • Product Roadmap
  • System Design
  • Data Science
  • Data Engineering
  • DevOps
  • Cross-Functional Collaboration
  • Stakeholder Management
  • Engineering Leadership
  • Financial Services

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