AI Summary
Lead the design, implementation, and maintenance of ML Ops solutions using AWS services. Manage a geographically distributed team and collaborate with stakeholders. Proven experience in end-to-end lifecycle of ML Ops / GenAI platform build out in cloud.
Key Highlights
Lead the design, implementation, and maintenance of ML Ops solutions using AWS services
Manage a geographically distributed team and provide technical directions
Collaborate with stakeholders, including data scientists, data engineers, and business stakeholders
Technical Skills Required
Benefits & Perks
Flexible Hybrid Work Arrangement
Relocation Assistance
Video Interview Option
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, RAVIN IT SOLUTIONS, Inc, is seeking the following. Apply via Dice today!
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