AI ML Architect

Job Description

Role & responsibilities Design robust and scalable AI/ML architectures that support the development and deployment of machine learning models and AI solutions. Develop and guide the implementation of end-to-end AI/ML solutions, including model development, data processing, and system integration. Evaluate and recommend the latest AI/ML technologies, frameworks, and tools to enhance system capabilities and performance. Collaborate with software engineers and other development teams to integrate AI/ML solutions into existing systems and applications. Ensure seamless operation and performance. Work with cross-functional teams, including developers, data scientists, machine learning engineers, and business stakeholders, to understand requirements and design solutions that align with business objectives. Create and maintain comprehensive documentation for AI/ML architectures, including design specifications, deployment procedures, and best practices. Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective Ensure that AI/ML systems comply with security standards and regulatory requirements. Implement best practices for data privacy and protection. Preferred candidate profile Bachelors degree in computer science, Data Science, Statistics, or a related field or a master's degree or higher is preferred. Total 10-15 years of industry experience More than 3 years of experience in designing and implementing AI/ML architectures, with a proven track record of successful projects. Extensive experience with machine learning frameworks (e.g., Go, TensorFlow, PyTorch), programming languages C#, .Net, NodeJS and data processing tools. Strong understanding of system architecture principles, including distributed systems, microservices, and cloud computing. Experience with Microsoft Azure cloud services and their AI/ML offerings Experience with event-handling systems such as Kafka Experience with big data technologies and data engineering practices. Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.