AI Architect

TxMinds


Date: 2 weeks ago
City: Remote
Contract type: Full time
Remote
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

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