Data Scientist AI/ML

As an AI/ML Solutions Developer at our company, you will be responsible for designing, developing, and optimizing AI/ML solutions using Snowflake Cortex and Cortex Code. Your key responsibilities will include: - Leading the implementation of chatbot solutions leveraging Snowflake's native AI capabilities to reduce dependency on pre-verified and hard-coded queries. - Improving SDLC efficiency through AI-driven development, automation, and intelligent workflows. - Developing GenAI-based code generation and optimization frameworks within the Snowflake ecosystem. - Automating testing processes and implementing AI-powered mechanisms to enhance data quality and validation. - Designing and implementing fuzzy logic-based validation frameworks to identify and enforce business rules that are not explicitly defined. - Building AI-driven solutions to convert logical data models into physical implementations, thereby accelerating data engineering and architecture processes. - Collaborating with data engineers, architects, and business stakeholders to define and implement scalable AI solutions. - Monitoring, evaluating, and continuously improving the performance, accuracy, and reliability of AI/ML models and applications. In order to be successful in this role, you should possess the following skills and qualifications: - Strong experience with Snowflake, including Snowflake Cortex and Cortex Code. - Expertise in AI/ML, Generative AI, and Large Language Model (LLM)-based applications. - Experience in building conversational AI/chatbot solutions. - Proficiency in Python, SQL, and data engineering concepts. - Knowledge of automated testing frameworks and data quality management. - Experience with fuzzy matching, fuzzy logic, and intelligent validation techniques. - Strong understanding of data modeling, metadata management, and data architecture. - Ability to translate business requirements into scalable AI-driven solutions. Additionally, having the following preferred qualifications would be advantageous: - Experience in implementing enterprise-scale GenAI solutions. - Familiarity with MLOps, CI/CD pipelines, and SDLC automation. - Experience in data governance, data quality, and model-driven development approaches. - Knowledge of cloud platforms such as AWS, Azure, or GCP. With 6-10 years of experience in software development and exposure to team handling, you will be well-equipped to excel in this role. As an AI/ML Solutions Developer at our company, you will be responsible for designing, developing, and optimizing AI/ML solutions using Snowflake Cortex and Cortex Code. Your key responsibilities will include: - Leading the implementation of chatbot solutions leveraging Snowflake's native AI capabilities to reduce dependency on pre-verified and hard-coded queries. - Improving SDLC efficiency through AI-driven development, automation, and intelligent workflows. - Developing GenAI-based code generation and optimization frameworks within the Snowflake ecosystem. - Automating testing processes and implementing AI-powered mechanisms to enhance data quality and validation. - Designing and implementing fuzzy logic-based validation frameworks to identify and enforce business rules that are not explicitly defined. - Building AI-driven solutions to convert logical data models into physical implementations, thereby accelerating data engineering and architecture processes. - Collaborating with data engineers, architects, and business stakeholders to define and implement scalable AI solutions. - Monitoring, evaluating, and continuously improving the performance, accuracy, and reliability of AI/ML models and applications. In order to be successful in this role, you should possess the following skills and qualifications: - Strong experience with Snowflake, including Snowflake Cortex and Cortex Code. - Expertise in AI/ML, Generative AI, and Large Language Model (LLM)-based applications. - Experience in building conversational AI/chatbot solutions. - Proficiency in Python, SQL, and data engineering concepts. - Knowledge of automated testing frameworks and data quality management. - Experience with fuzzy matching, fuzzy logic, and intelligent validation techniques. - Strong understanding of data modeling, metadata management, and data architecture. - Ability to translate business requirements into scalable AI-driven solutions. Additionally, having the following preferred qualifications would be advantageous: - Experience in implementing enterprise-scale GenAI solutions. - Familiarity with MLOps, CI/CD pipelines, and SDLC automation. - Experience in data governance, data quality, and model-driven development approaches. - Knowledge of cloud platforms such as AWS, Azure, or GCP. With 6-10 years of experience in software development and exposure to team handling, you will be well-equipped to excel in this role.