ML Architect

Godrej Enterprises Group:

Godrej Enterprises Group (comprising Godrej & Boyce and its subsidiaries) has a significant presence across diverse consumer and industrial businesses spanning Aerospace, Aviation, Defence, Engines and Motors, Energy, Locks & Security Solutions, Building Materials, Green Building Consulting, Construction and EPC Services, Heavy Engineering, Intralogistics, Tooling, Healthcare Equipment, Consumer Durables, Furniture, Interior Design, Architectural Fittings, IT solutions and Vending Machines.

KRA:

• Develop and implement a robust and scalable AI/ML architecture that aligns with business objectives.
• Ensure cost-effectiveness of the AI/ML infrastructure.
• Prototype and experiment with novel AI/ML techniques and applications.
• Conduct regular audits and assessments of solutions.
• Develop and publish evaluation metrics.
• Contribute to presentation, content, awareness building and training of AI/ML.

Job Description:

Develop and implement a robust and scalable AI/ML architecture that aligns with business objectives.

• Design, develop, and architect scalable and robust AI/ML solutions and help productionize the workloads.
• Define and enforce AI/ML architecture standards and best practices including MLOps.
• Help improve accuracy and robustness for AI systems developed.
• Implement model monitoring and performance optimization strategies. Ensure model scalability and reliability in production environments.
• Enable innovation, efficiency, and competitive advantage through AI/ML.

Cost-effectiveness of the AI/ML infrastructure.

• Define the overall AI/ML architecture roadmap and practices.
• Research and analyze to identify emerging AI architecture, techniques, and accuracy improvement trends and patterns.
• Drive AI/ML/MLOps architecture definition and guidance on developing solutions.
• Maintain a competitive edge and explore new business opportunities.
• Contribute to infrastructure architecture for ML model training and deployment.

Prototype and experiment with novel AI/ML techniques and applications.

• Define the overall AI architecture roadmap and MLOps practices.
• Work on prototypes.
• Implement new techniques successfully.
• Drive innovation and research in AI/ML to identify and implement cutting-edge solutions.

Conduct regular audits and assessments of solutions.

• Establish an auditing framework with scoring methods and execute it.
• Ensure compliance with ethical guidelines and regulations.
• Reduce bias and fairness issues in models.
• Conduct code reviews and architecture assessments using standard techniques and best practices.

Develop and publish evaluation metrics.

• Design and implement an AI auditing framework.
• Evaluate and select appropriate AI models and frameworks and assist in evaluating POCs.

Contribute to presentation, content, awareness building and training of AI/ML.

• Develop presentations and content.
• Build awareness and communication.
• Conduct training and capability building.
• Establish metrics and evaluation.

Requisite Qualification:

BE/BTech (Computer Application/Information & Technology/AI/Electronics and Telecommunication).

Certification in AI/ML, extensive training in AI/ML, MLOps, and AI Platforms.

Certification in cloud technologies (Azure/AWS).

Essential Experience:

8-10 years of experience, with a minimum of 5-6 years in AI/ML and a background in Cloud Architecture.

Skills Required:

Functional Skills:

Deep Learning & Core AI/ML: Strong understanding of neural networks, deep learning frameworks, and fundamental machine learning concepts.

AI & MLOps: Proficiency in AI, ML development frameworks, and hands-on cloud expertise.

Cloud & Software Architecture: Proficiency in cloud platforms (AWS, Azure, GCP), scalable software architecture, and API design.

Data & AI Engineering: Experience with data pipelines, data management, and a strong understanding of ethical AI considerations.

Model Expertise: In-depth knowledge of AI algorithms, models, and libraries.

Knowledge of frameworks (TensorFlow, PyTorch, etc.) and neural network architectures.

Python Programming: Advanced Python skills with relevant AI libraries.

AI & General Software Architecture: Ability to design scalable AI systems.

Cloud Computing Architecture: Experience with cloud platforms and AI services (AWS, Azure, GCP).

Data Engineering Skills: Knowledge of data pipelines and big data technologies.

Model Optimization & Deployment: Experience in performance optimization and production deployment.

Excellent knowledge of methodologies, processes, and tools associated with supporting this function effectively.

Soft Skills:

• Ability to translate business needs into technical solutions and effectively communicate complex concepts to diverse audiences.
• Excellent interpersonal skills, comfortable working at all levels within an organization and in a wide variety of situations.
• Self-motivating and able to work under own initiative.
• Professional with a strong work ethic.
• Able to thrive in a dynamic and changing environment.
• Diplomatic with the ability to interact successfully with all levels of the business.
• Questions the status quo and navigates through roadblocks.