Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Python (Programming Language)
Good to have skills : NA
Minimum 2 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: The Backend Engineer focuses on developing and maintaining the server-side components of the simulation system, ensuring robustness, scalability, and performance. Roles & Responsibilities: - Expected to perform independently and become an SME. - Required active participation/contribution in team discussions. - Contribute in providing solutions to work-related problems. - Design and develop back-end components and APIs for simulation. - Ensure high performance, reliability, and scalability of server-side components. - Implement security and data protection measures. - Collaborate with front-end engineers to integrate front-end and back-end components. - Troubleshoot and resolve back-end issues related to simulation. - Develop applications and systems utilizing AI tools and Cloud AI services. - Create a proper cloud or on-prem application pipeline with production-ready quality. Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language). - Strong expertise in back-end development (Java, Python, Node.js, etc.). - Proficiency with back-end frameworks and tools. - Experience in building and optimizing APIs for simulation systems. - Good understanding of database systems and data storage solutions. - Ability to troubleshoot and optimize complex systems. - Strong understanding of statistical analysis and machine learning algorithms. - Experience with data visualization tools such as Tableau or Power BI. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: - A 15 years full-time education is required.

15 years full time education

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