GenAI Architect

GenAI Architect Job Summary

As a Technical Specialist in Machine Learning, you will play a critical role in conceptualizing, designing, and delivering innovative solutions that drive product excellence and sustainment delivery. You will leverage your advanced expertise in Machine Learning, Tensor Flow, PyTorch, and Python to ensure that the solutions not only meet but exceed client expectations while adhering to the highest quality standards.

• Architect And Design Machine Learning Solutions Using Tensorflow And Pytorch, Guiding The Development Process Through The Team To Ensure Product And Project Deliverables Align With Defined Scope And Standards.
• Act As A Subject Matter Expert (Sme) In Machine Learning, Providing Technical Guidance And Support To The Team And Stakeholders Throughout The Project Lifecycle.
• Ensure Continuous Knowledge Enhancement By Exploring And Integrating New Technologies And Methodologies In Machine Learning, Maintaining The Relevance And Quality Of Solutions Delivered To Clients.
• Train And Mentor Team Members In Machine Learning Concepts And Tools, Fostering A Skilled Workforce That Effectively Mitigates Delivery Risks And Enhances Project Outcomes.
• Gather Project Specifications And Deliver Tailored Machine Learning Solutions By Leveraging Domain Knowledge And Technical Expertise To Meet Client Requirements Effectively.
• Review And Evaluate Project Deliverables, Ensuring They Meet Established Quality Criteria And Align With Industry Best Practices In Machine Learning.
• Recommend And Implement Client Value Creation Initiatives By Applying Industry Best Practices In Machine Learning, Contributing To The Strategic Goals Of The Organization.

• Expert Proficiency In Machine Learning Frameworks Such As Tensorflow And Pytorch.
• Strong Programming Skills In Python, With A Good Understanding Of Associated Libraries And Tools.
• Solid Experience In Sql For Data Manipulation And Management.
• In-Depth Knowledge Of Machine Learning Algorithms And Model Development Processes.
• Familiarity With Data Preprocessing, Feature Engineering, And Model Evaluation Techniques