Ai Lead Job in Telerad Tech

Required skills

• Very strong Graduate/Ph.D. level degree in Computer Science/or other engineering discipline from top tier schools
• Relevant experience of 8-12 years on live industry projects at enterprise level
• Extremely strong in Python Programming, Tensor flow, Sci-kit learn, Keras, Theano, and other relevant Python Libraries for AI & Machine Learning (Scikit learn, NLTK, Scipy, etc.). Scale of 8/9 on 10.
• Strong ability to manipulate data using Pandas/Numpy and other python libraries, Should be able to support all data munging and cleansing activities as part of guiding and leading an AI-platform implementation team
• Experience in working in Agile methodology in a very high performance coding environment with high level of automation.
• Strong hands-on skills in relational data bases. Ability to write SQL like queries to create new joins or data frames with a goal of framing the right business questions for the AI platform development team
• Ability to white board with clients all types of possible solutions end-to-end (front end- API s and Back end).
• Good handle on concepts of enterprise application architecture, solution architecture and enterprise architecture

Tools & Technologies

Key Responsibilities

• Ideate and formulate a pragmatic blueprint for enterprise AI platform solution and subsequent development using Deep learning with a cross-functional team of talented engineers, Motivated self-learner
• Collaborate well with engineers, researchers, and data implementation specialists to design and create advanced, elegant and efficient AI based solutions for business problems
• Provide real time knowledge transfer to the team on the Requirements based on client facing meetings and white boarding workshops
• Help in writing a comprehensive proposal with the help of the other engineers on the project
• Work in an agile environment based on the defined sprint backlogs to deliver the assigned work in the stipulated timelines.
• Adhere to software development best practices and coding standards in all work products and participate in the refinement of those practices and standards to improve quality and productivity.