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14 Weeks ago

Lead Analyst - AI Engineer (Full Stack)

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Bangalore, Karnataka, India
Information Technology
Other
Eaton

Overview

What you’ll do:

  • Must have proven experience in Building front-end and back-end components for AI applications, building/consuming APIs, building customer centric user interfaces and designing integrations with other systems using .Net, JavaScript, Angular or React, SQL
  • Must have proven experience in solution deployment by packaging trained AI models as services using Azure deployment services, Kubernetes, and GitHub for version control.
  • Should have in depth understanding of Azure AI services such as Azure Machine Learning and Cognitive Services along with other AI technologies, natural language processing (NLP), computer vision and GPT models
  • Should have strong expertise in articulating and documenting solution architecture for AI projects by collaborating with solution architect and enterprise architects.
  • Must have abilities to collaborate with business leaders to understand their pain points and identify key areas where AI solutions can drive significant business benefit.
  • Must have strong analytical and problem-solving skills, with the ability to translate business requirements into effective AI solutions.
  • Must have excellent communication skills, with the ability to convey complex AI technical concepts to non-technical stakeholders


Qualifications:

Bachelors in engineering/ B.E/B. Tech and/or required equivalent MCA.
2.Overall 10+ years’ experience with proven track record of 5+ years in Solutioning and deploying end to end AI
3.Technical skills : Net, JavaScript, Angular or React, SQL Server, Azure deployment services, Kubernetes, GitHub , Azure Cognitive Services , GPT models, added advantage with GitHub Copilot

Skills:

  • Proficiency in front-end technologies (React or Angular) and back-end technologies (e.g., Node.js, Python, .NET).
  • Strong understanding of AI and machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Experience with cloud and hybrid infrastructures.
  • Proficiency in scripting and automation tools (e.g., PowerShell, Azure CLI)
  • Expertise in cloud native development specialized in Microsoft Azure tech stack
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