AI Lead/Architect

Key Responsibilities :-

• Design and Implement Artificial Intelligence and Data Science solutions on Cloud at enterprise scale.
• Contextual understanding of customer requirements with visions, strategies, and roadmaps for implementation.
• Collaboration with solution architect, business analysts and partner architects/stakeholders in Global Delivery model for AI Solution development
• Play a key role in defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings. Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools.
• Audit AI tools and practices across data, models and software engineering with a focus on continuous improvement
  
  

Technical Qualifications :

• Understand the workflow and pipeline architectures of ML and deep learning workloads
• .Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow) and ML techniques (such as random forest and neural networks).
• Hands-on programming skill on at least one language C#.net or node.js or python.
• Expert on Cloud competencies on “Artificial Intelligence” and “Machine Learning” PaaS components:•
• Contextual Conversation design (Azure BOT service/Amazon Lex/ Google Dialog flow) – for personalized and humanized interaction with end user for complex business cases•
• Natural Language Processing model design, training and publishing for multiple languages• Emotion and Sentiment Analytics•
• Custom Speech model - Speech-to-text and Voice synthesis calibrated for language, accent, pitch, tone, noise and business vocabs.• Computer vision - OCR, Face Recognition, Custom model for Object detection and classifications•
• Document/Form Entity Extraction• Cognitive Search on heterogeneous unstructured data• Enterprise Channel Integration for AI •
• Deployment and publish for AI and ML services with ACR, ACI, Docker, Azure Kubernetes• Azure/ AWS/ GCP/ Watson certifications on AI & Data Science like AI 102, DP 100.•
• Enterprise cloud Data repository –Cloud Storage, NoSQL DB, Graph DB, Data Lake• Data Ingestion, Transformation, Analytics – Real-time and batches•
• Enterprise Security for AI/ML - Active Directory - Authentication, Authorization• Web app and services – Micro services, Azure functions, Logic apps, API management- Ability to compare and contrast across technologies in any layer objectively with evaluation criteria and considerations
• Excellent communication skills, preparing PowerPoint presentations, executive readouts