Role Overview: As a Data Scientist in this contract to hire position, you will utilize your expertise in Java and Python programming to develop, train, and deploy advanced AI models and solutions focusing on Generative AI (GenAI) and Vertex AI. Your role will involve enhancing automation, analytics, and decision-making capabilities across the organization. Key Responsibilities: - Design, build, and deploy AI/ML and GenAI models using Vertex AI and related tools. - Develop and optimize scalable data pipelines and model training workflows. - Implement coding solutions in Java and Python for model integration and automation. - Collaborate with cross-functional teams to identify, design, and deliver AI-driven solutions. - Evaluate model performance, perform fine-tuning, and ensure production readiness. - Stay updated on emerging AI/ML trends, frameworks, and technologies to enhance solution quality. Qualification Required: - 7-9 years of experience in AI/ML or Data Science roles. - Strong proficiency in Java and Python for data modeling and automation. - Hands-on experience with Generative AI frameworks and Vertex AI for model development and deployment. - Solid understanding of machine learning algorithms, data processing, and cloud environments. - Experience in integrating models with business systems and APIs. - Strong analytical, problem-solving, and collaboration skills. Role Overview: As a Data Scientist in this contract to hire position, you will utilize your expertise in Java and Python programming to develop, train, and deploy advanced AI models and solutions focusing on Generative AI (GenAI) and Vertex AI. Your role will involve enhancing automation, analytics, and decision-making capabilities across the organization. Key Responsibilities: - Design, build, and deploy AI/ML and GenAI models using Vertex AI and related tools. - Develop and optimize scalable data pipelines and model training workflows. - Implement coding solutions in Java and Python for model integration and automation. - Collaborate with cross-functional teams to identify, design, and deliver AI-driven solutions. - Evaluate model performance, perform fine-tuning, and ensure production readiness. - Stay updated on emerging AI/ML trends, frameworks, and technologies to enhance solution quality. Qualification Required: - 7-9 years of experience in AI/ML or Data Science roles. - Strong proficiency in Java and Python for data modeling and automation. - Hands-on experience with Generative AI frameworks and Vertex AI for model development and deployment. - Solid understanding of machine learning algorithms, data processing, and cloud environments. - Experience in integrating models with business systems and APIs. - Strong analytical, problem-solving, and collaboration skills.

As a Gen AI Engineer, your role will involve designing and optimizing scalable AI systems. You will work with large datasets, utilize advanced statistical modeling techniques, and develop large language models (LLMs) using Python. There will also be opportunities for you to explore Agentic AI. Key Responsibilities: - Design, implement, and manage large-scale data and AI solutions. - Develop and fine-tune statistical and machine learning models for real-world applications. - Build, optimize, and deploy LLMs using Python and related frameworks. - Conduct performance tuning and optimization of complex AI systems. - Collaborate cross-functionally with data scientists, ML engineers, and business stakeholders to deliver impactful AI-driven solutions. - (Optional but desirable) Contribute to experimental or production-level projects in Agentic AI. Required Skills & Qualifications: - Strong background in implementing large-scale data and AI systems. - Proficiency in advanced statistical modeling and machine learning techniques. - Hands-on experience developing and deploying LLMs using Python. - Expertise in optimizing performance for high-scale AI applications. - Familiarity with ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). - Excellent problem-solving and communication skills. As a Gen AI Engineer, your role will involve designing and optimizing scalable AI systems. You will work with large datasets, utilize advanced statistical modeling techniques, and develop large language models (LLMs) using Python. There will also be opportunities for you to explore Agentic AI. Key Responsibilities: - Design, implement, and manage large-scale data and AI solutions. - Develop and fine-tune statistical and machine learning models for real-world applications. - Build, optimize, and deploy LLMs using Python and related frameworks. - Conduct performance tuning and optimization of complex AI systems. - Collaborate cross-functionally with data scientists, ML engineers, and business stakeholders to deliver impactful AI-driven solutions. - (Optional but desirable) Contribute to experimental or production-level projects in Agentic AI. Required Skills & Qualifications: - Strong background in implementing large-scale data and AI systems. - Proficiency in advanced statistical modeling and machine learning techniques. - Hands-on experience developing and deploying LLMs using Python. - Expertise in optimizing performance for high-scale AI applications. - Familiarity with ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). - Excellent problem-solving and communication skills.

As a Data QA Engineer, you will play a crucial role in ensuring the accuracy and reliability of data through ETL testing, data validation, and dashboard verification. Your strong expertise in SQL, ETL layers validation, and automation-driven approach will be key to success in this role. **Key Responsibilities:** - Perform comprehensive end-to-end testing of ETL pipelines and data workflows. - Validate data integrity across various ETL layers including Source, Staging, Curated, and Reporting. - Utilize advanced SQL skills to execute complex queries for data validation and reconciliation purposes. - Validate Snowflake tables, views, transformations, and stored procedures to maintain data accuracy. - Conduct dashboard validation by comparing Tableau dashboards with Snowflake data to ensure consistency. - Perform data reconciliation checks to guarantee accuracy and completeness. - Develop and maintain automated data validation frameworks for efficient testing processes. - Conduct regression testing for data releases and schema changes to identify potential issues. - Collaborate with Data Engineers to address and resolve data quality defects effectively. - Create detailed test documentation, test cases, and validation scripts to support testing activities. **Qualifications Required:** - Strong background in ETL Testing and Data Validation. - Proficient in advanced SQL concepts including joins, aggregations, window functions, and complex queries. - Hands-on experience in validating data across multiple ETL layers. - Familiarity with Snowflake data warehouse validation processes. - Experience in testing Tableau dashboards and reports. - Sound knowledge of data reconciliation techniques. - Previous exposure to regression testing in data pipelines. - Excellent analytical and problem-solving skills. - Domain experience in BFSI/Financial domain is preferred. **Additional Details:** - Preferred Skills: - Experience with cloud platforms like AWS, Azure, or GCP. - Proficiency in data testing tools and automation frameworks. - Exposure to dbt testing frameworks. - Familiarity with modern data warehouse environments. This role offers you the opportunity to work with cutting-edge technologies and make a significant impact on data quality assurance processes in a dynamic environment. As a Data QA Engineer, you will play a crucial role in ensuring the accuracy and reliability of data through ETL testing, data validation, and dashboard verification. Your strong expertise in SQL, ETL layers validation, and automation-driven approach will be key to success in this role. **Key Responsibilities:** - Perform comprehensive end-to-end testing of ETL pipelines and data workflows. - Validate data integrity across various ETL layers including Source, Staging, Curated, and Reporting. - Utilize advanced SQL skills to execute complex queries for data validation and reconciliation purposes. - Validate Snowflake tables, views, transformations, and stored procedures to maintain data accuracy. - Conduct dashboard validation by comparing Tableau dashboards with Snowflake data to ensure consistency. - Perform data reconciliation checks to guarantee accuracy and completeness. - Develop and maintain automated data validation frameworks for efficient testing processes. - Conduct regression testing for data releases and schema changes to identify potential issues. - Collaborate with Data Engineers to address and resolve data quality defects effectively. - Create detailed test documentation, test cases, and validation scripts to support testing activities. **Qualifications Required:** - Strong background in ETL Testing and Data Validation. - Proficient in advanced SQL concepts including joins, aggregations, window functions, and complex queries. - Hands-on experience in validating data across multiple ETL layers. - Familiarity with Snowflake data warehouse validation processes. - Experience in testing Tableau dashboards and reports. - Sound knowledge of data reconciliation techniques. - Previous exposure to regression testing in data pipelines. - Excellent analytical and problem-solving skills. - Domain experience in BFSI/Financial domain is preferred. **Additional Details:** - Preferred Skills: - Experience with cloud platforms like AWS, Azure, or GCP. - Proficiency in data testing tools and automation frameworks. - Exposure to dbt testing frameworks. - Familiarity with modern data warehouse environments. This role offers you the opportunity to work with cutting-edge technologies and make a significant impact on data quality assurance processes in a dynamic environment.