Job description

This role will be responsible for implementing AI and machine Learning solutions on cloud-based platforms, exploring emerging trends in AI, developing proofs-of-concept, and engaging with the internal and external ecosystem to progress the proof of concepts to production. This role would also involve applying engineering principles from the classical software development lifecycle to AI and machine Learning. Key Responsibilities - Develop AI & Machine Learning solutions on cloud-based platforms. - Discover data sources, get access to them, import them, clean them up, and convert them to trainable format. - Ability to understand & implement research papers, custom models. - Build backend systems that interact with other microservices. - Train and optimize machine learning models. - Engineer machine intelligence systems and infrastructure for real-world production use at scale. - Should be able to understand the problem statement and be able to justify the usage of AI/ML as a... solution. - Be able to quickly prototype and provide results. - Explore data features and manipulate data with SQL and scripts. - Partner with internal (FIL teams) & external ecosystems to design and deliver AI & ML solutions. - Explore emerging trends in AI & Machine learning and develop prototypes. - Effective communication and teamwork skills. Experience And Qualifications Required - Strong working experience in a variety of analytical techniques including data pre-processing, basic ML techniques & other advanced models like in Deep Learning. - Good Experience in model building & optimization and data visualization. - Excellent knowledge and good practical skills in major ML algorithms as applied to Natural Language Processing and Computer Vision & Graph Networks. - Strong experience in developing AI & Machine Learning solutions on cloud platforms like AWS / Microsoft Azure. - Good understanding of SQL query development. - Familiarity with data platforms like Snowflake would be an added advantage. - Familiarity with MLOps (Machine Learning Operations) would be an added advantage. - Familiarity with advanced Computer Vision model development would be an added advantage. - Practical experience with deep learning projects is highly valued. - Ability to improve the accuracy, runtime, scalability, and reliability of machine intelligence systems. - Strong in understanding underlying math and algorithms. - Passion for continuing to learn state-of-the-art techniques in ML/Data science,

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