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Senior Artificial Intelligence/Machine Learning Engineer - Data Science


YO HR Consultancy


Location

Chennai | India


Job description

About the client:- Company Name: IT Company - Industries: IT Services & Consulting - Company Type: Forbes Global 2000 - Funding Stage: Series C - Headquarter Location: US - Nature of Offering: Product & Services - Founding Year: 2010 - No of Employees: 1001-5000 Role : Senior AI/ML EngineerLocation : RemoteExperience : 7 to 11 yearsMust have :- Experience in computer vision- Experience in Python.- Experience in TensorFlow or PyTorch- Knowledge of text detection & OCR, human / face detection, generative models, video analytics, model compression / optimization. - Experience in SAAS DomainRoles & Responsibilities :Role :- The role is of a Senior AI Engineer and responsible for developing scalable solutions using AI tools.- To understand business requirements, convert them into analytical questions effectively and provide meaningful recommendations.- Perform research, data analysis and testing to develop machine learning algorithms and predictive models.- Build the Data Pipeline Management (DPM) for respective Use-Cases.- One needs to test, tune, integrate, package and monitor solutions throughout the ML Cycle.- Work on daily tasks to complete them effectively to meet the project goals and timelines.- Resolve post production issues based on the activities related to monitoring the model decay, data drift and apply Retraining approaches to ensure respective KPI's are constantly met.Responsibilities :- Deliver robust, well-tested, and fully documented modules to serve the use cases- Implement state-of-the-art deep learning algorithms to support people and product association- Collaborate within the AI team and interlocked team.- Continuously improve the efficiency and robustness of existing modules- Work with engineering team to implement the entire application modules as discoverable microservices, experience hosting and deploying ML solutions- Perform code reviews and ensuring proper design and delivery- Promote best practices and establish team processes- Identify infrastructure and architectural investment needs. (ref:hirist.tech)


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