ATLANTA, GA, USA
61 days ago
AI/ML Solutions Architect with GCP - Hybrid, Atlanta

 

We currently have a career opportunity for a AI/ML Senior Solutions Architect with Google Cloud Platform (GCP) to join our Data Solutions Team.  This position will be in Atlanta and work 3 days in the office and 2 days remote for the first 6 months.

As an AI/ML Data Solutions Architect, you will provide best-fit architectural solutions for one or more projects; you will assist in defining scope and sizing of work; and anchor Proof of Concept developments. You will provide solution architecture for the business problem, platform integration with third party services, designing and developing complex features for clients' business needs.

The Solutions Architect will provide technology direction, ensures project implementation compliance, and utilizes technology research to innovate, integrate, and manage technology solutions.  You will collaborate with some of the best talent in the industry to create and implement innovative high-quality solutions, participate in Sales and various pursuits focused on our clients' business needs.

Job Overview:

The role of this Senior Solutions Architect is for individuals passionate about identifying and delivering the right Business solution for each client using Gen AI, AI/ML and NLP.   Will are keen to understand our customer needs, processes and pain points to determine the success factors and evaluation criteria that will be needed to measure the effectiveness of a GenAI, ML and NLP model.

The Solutions Architect will be involved in the strategic planning of an engagement or helping the client make decisions about their future Gen AI, AI/ML roadmap and vision. Once the project has begun, will be responsible for the execution of our established methodology, work with customer and/or the teams data engineer to identify data ingestion and transformation needs, exploration of the data and reporting findings, modeling and evaluation of training iterations. It is a key part of the role to be able to explain in non-technical terms the chosen modeling approach and findings from data exploration or training results.

 

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