Coforge
Role : AI Architect
Location : Chicago, IL
Skills : AI/ML Models and Algorithms, GenAI
Experience:
15 + Years
We at Coforge are seeking an AI Architect with proven experience in developing data and services in an enterprise and cloud environment. The ideal candidate will have extensive experience Design and Implement AI/ML Models and Algorithms and Expertise in Data Architecture. Responsibilities: Lead the design and implementation of end-to-end AI systems. Take foundational models from existing platforms and fine-tune them with data to achieve specific outcomes. Lead the implementation of best practices for deploying and serving various types of AI models. Provide expertise in ML practices, CI/CD pipelines, and infrastructure to automate the deployment, versioning, and lifecycle management. Architect and deploy AI solutions on AWS and other major cloud platforms, with a hands-on emphasis on using cloud-native services for computation, storage, and networking. Utilize exceptional proficiency in Python and other relevant languages to build high-performance, production-ready AI services and tools. Performance Tuning: Design and implement monitoring and alerting solutions to evaluate model performance, data drift, and system health in production. Lead and mentor a team of engineers, guiding architectural decisions, ensuring code quality through rigorous code reviews, and establishing best practices for development.
Required Skills: Proven experience in developing data and services in an enterprise and/or cloud environment. Good experience with GenAI Lead the Architecture and Design: Translate Business Needs/ QE needs into AI Solutions: Design and Implement AI/ML Models and Algorithms: Data Architecture Expertise: Collaborate and Lead: Deep understanding of AI systems, model governance, and risk frameworks. Proficiency in relevant technologies and languages such as Databricks, Azure data services, Oracle, Postgres, SQL Server, SQL, Java, Python, Scala. Strong working knowledge of data engineering technologies, data modelling tools, and ETL strategies. Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders
15 + Years
We at Coforge are seeking an AI Architect with proven experience in developing data and services in an enterprise and cloud environment. The ideal candidate will have extensive experience Design and Implement AI/ML Models and Algorithms and Expertise in Data Architecture. Responsibilities: Lead the design and implementation of end-to-end AI systems. Take foundational models from existing platforms and fine-tune them with data to achieve specific outcomes. Lead the implementation of best practices for deploying and serving various types of AI models. Provide expertise in ML practices, CI/CD pipelines, and infrastructure to automate the deployment, versioning, and lifecycle management. Architect and deploy AI solutions on AWS and other major cloud platforms, with a hands-on emphasis on using cloud-native services for computation, storage, and networking. Utilize exceptional proficiency in Python and other relevant languages to build high-performance, production-ready AI services and tools. Performance Tuning: Design and implement monitoring and alerting solutions to evaluate model performance, data drift, and system health in production. Lead and mentor a team of engineers, guiding architectural decisions, ensuring code quality through rigorous code reviews, and establishing best practices for development.
Required Skills: Proven experience in developing data and services in an enterprise and/or cloud environment. Good experience with GenAI Lead the Architecture and Design: Translate Business Needs/ QE needs into AI Solutions: Design and Implement AI/ML Models and Algorithms: Data Architecture Expertise: Collaborate and Lead: Deep understanding of AI systems, model governance, and risk frameworks. Proficiency in relevant technologies and languages such as Databricks, Azure data services, Oracle, Postgres, SQL Server, SQL, Java, Python, Scala. Strong working knowledge of data engineering technologies, data modelling tools, and ETL strategies. Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders