MLOps Lead

Fractal Analytics•New York, NY

1d•$140,000 - $205,000•Remote

About The Position

Building the machine learning production System (or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. This position is an opportunity for an experienced, server-side developer to build expertise in this exciting new frontier. You will be part of a team deploying state-of-the-art AI solutions for Fractal clients.

Requirements

15+ years of experience building engineering and data-science businesses across various technologies
Deep technical skills along with strong client and market orientation
Experience or expertise in building and deploying machine-learning pipelines
Experience or expertise in cloud-based and hybrid deployments
Experience in Model repository (either of): MLFlow, Kubeflow Model Registry
Experience working across all phases of model development lifecycle to build MLOPs components
Experience with cloud-based technologies (AWS)
Experience building production grade LLM based solutions
Should be a visionary, should have experience in building large production systems
Prior experience engaging with CXO’s of client companies
Client Service Orientation, Ability to work with client leadership to develop solutions, build trust and deploy appropriate scalable solutions
Exhibits High learning orientation. Stay abreast of and share industry/technology trends relevant to the AI Machine learning discipline

Responsibilities

Based out of US, Leader for MLOPs will be the key leader in the AI@Scale practice.
The person will be responsible to architect and execute technology projects across client AI and Engineering engagements.
S/He will be accountable for building a trusted relationship, at middle and senior management across lines.
As the MLOps leader, S/he will support client projects, lead solution design, and contribute to the overall MLOps engineering using on-premise (open-source) or cloud-based (AWS) architectures
Act as a subject matter expert in machine-learning model deployment and MLOps pipelines – strong understanding of Machine-learning model building lifecycle, deployment, monitoring and production
Research and evangelize the use of GenAI, data-science and engineering solutions for strategic decision-making
Articulate business value and benefits of the technological solution to senior business and technology partners
Research, design and implement leading-edge MLOps architecture patterns to solve hard problems for the clients
Bring GenAI, data-science & engineering thinking to win large AI led digital transformation deals
Lead client delivery engagements.
Develop detailed business case, product roadmaps and financial justifications to quantify the business value of technological programs
Implement AI and engineering processes and governance methods to manage the risk of delivery
Help clients to define and design AI based solution architectures
Lead and energize the teams and clients by providing thought leadership in enterprise-grade machine-learning operations and modern cloud adoption patterns
Develop product roadmaps and help clients prioritize based on business objectives and impact