Overview
On Site
Depends on Experience
Full Time
Accepts corp to corp applications
Able to Provide Sponsorship
Skills
Amazon S3
Amazon Web Services
Cloud Computing
Collaboration
Artificial Intelligence
Amazon SageMaker
Communication
Continuous Integration
Documentation
Generative Artificial Intelligence (AI)
Jupyter
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Stakeholder Management
Version Control
Virtual Team
Python
Product Management
Job Details
Job Description: ML Ops Lead /Architect*
Client Name : Bank
Mode of Work - Flexible Hybrid (Edison NJ /Toronto ON)
Video Interview (Relocation works)
Over all 14+ years of experience for an Architect.
Please share resume with linkedin details
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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.