AI / ML Engineer

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 : Machine Learning
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : BE

Summary: As an AI/ML Engineer, you will be responsible for developing applications and systems that utilize AI to improve performance and efficiency. Your typical day will involve working with machine learning algorithms, deep learning, neural networks, chatbots, and natural language processing. Roles & Responsibilities: - Convert a business problem into a data driven ML solution. - Develop, Manage, architect ML and advanced analytics models. - Examine data from multiple sources and share insights. - Act as Subject Matter Expert in area of data science - Experiment design, evaluation, creation and analysis of dashboards/reports and evaluation, defining metrics - Product Leadership: influencing product teams through presentation of data-based recommendations, communicating state of business, experiment results. - Design and develop machine learning models and algorithms for various applications. - Implement and optimize deep learning models and neural networks. - Develop chatbots and natural language processing systems. - Collaborate with cross-functional teams to integrate AI solutions into existing systems. - Stay updated with the latest advancements in AI and machine learning technologies. Professional & Technical Skills: - End to end knowledge of Life Cycle of ML Model. Strong understanding of machine learning algorithms and techniques. - Hands on experience in Python and PySpark, TensorFlow, Keras, PyTorch, and other machine learning frameworks. - Expertise in Python to deploy ML and Advanced analytics models - Experience with deep learning, neural networks, chatbots, and natural language processing. - Use of Python as Data Science tool kit. - Strong Programming skill in Python for Data ETL activities and in Java, or C++. - Ability to derive insights from analytical and ML models - Knowledge of Statistics: hypothesis testing, regression - Data Infrastructure: Hadoop and Hive, MySQL, Oracle, Vertica and automating analyses and authoring pipelines via SQL - Experience with data analysis and visualization tools such as Tableau or Power BI. - Must To Have Skills: - Good To Have Skills: Experience with cloud-based AI services such as AWS, Azure, or Google Cloud. Additional Information: - The candidate should have a minimum of 12 years of experience in machine learning. - The ideal candidate will possess a strong educational background in statistics, mathematics, computer science, or a related field.

BE

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