AI/ML Lead (Sagemaker)
- Toronto, ON, Canada
Contract
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Job details
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- Contract
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- Posting language
- English
- Posted
Original job description
Iris's client, one of the world's largest multinational Investment banking and financial services corporations, is looking to hire an AI/ML Lead opportunity.
Work location: Toronto, ON / Halifax / Jersey City, NJ / Chicago, IL (Hybrid Onsite – 2 to 3 days a week office) – (any work location is fine)
Mandatory skills: Sagemaker, AWS, AI/ML
ML Ops / AI Platform technical product lead/ manager
Job description:
- Require a 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.
Good fit if individual has:
- 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.
More about this job
Responsibilities
Lead the design, implementation, and maintenance of cloud-based MLOps solutions, including platforms built with Amazon SageMaker and other AWS services. 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
The role calls for extensive experience building and managing cloud-based MLOps or GenAI platforms, preferably on AWS, along with technical product or cloud platform leadership experience. Candidates should have hands-on cloud infrastructure experience and working knowledge of SageMaker, related AWS services, infrastructure as code, GitHub workflows, CI/CD, version control, and Python tooling.
Skills
- Amazon SageMaker
- AWS
- AI/ML
- MLOps
- AI Platform Leadership
- Technical Product Management
- Cloud Infrastructure
- System Design
- Stakeholder Management
- Team Leadership
- Amazon ECS
- AWS IAM
- Amazon CloudWatch
- Amazon S3
- AWS CDK
- Python
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Management & Leadership
- Data & Analytics
- Software
- Finance & Accounting
Keywords
- Amazon SageMaker
- AWS
- Artificial Intelligence
- Machine Learning
- MLOps
- GenAI
- Cloud Platform
- Cloud Infrastructure
- Technical Product Management
- Product Roadmap
- System Design
- Amazon ECS
- AWS IAM
- Amazon CloudWatch
- Amazon S3
- AWS CDK
- Infrastructure As Code
- GitHub Workflows
- CI/CD
- Version Control
- Python
- Jupyter Notebooks
- Software Packaging
- Technical Leadership
- Stakeholder Management
- Cross-Functional Collaboration
- Distributed Teams
- Investment Banking
- Financial Services