Solution Architect

Job Summary:

As an AI/ML Architect at Emerson, you will be responsible for designing and guiding the implementation of scalable, high-performance AI/ML architectures. You will work closely with developers, data scientists, engineers, and other stakeholders to ensure that our AI/ML solutions meet business needs and technological standards.

In This Role, Your Responsibilities Will Be:

• 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.

For This Role, You Will Need:

• Bachelor's 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.

Preferred Qualifications that Set You Apart:

• Prior experience in development of products is essential.
• Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to have
• Experience with AI/ML model versioning and life cycle management.
• Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Knowledge of AI ethics and responsible AI practices.