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Merkle Technologies

Gen AI Manager / AI Project Manager

Department
Engineering
Job Type / Location
Bengaluru
Experience Required
14+ years
Posted On

About the Role

We are seeking a GenAI Manager / AI Project Manager to join our team in Bengaluru, Pune, or Hyderabad. The ideal candidate will have extensive experience in Artificial Intelligence and Generative AI, with a proven track record in GenAI projects.

Roles and Responsibilities

  • Lead and execute GenAI projects, providing consultancy and driving delivery transformation of engineering projects leveraging AI/ML/Deep Learning and GenAI.
  • Become a trusted technical advisor within practices and influence the technology roadmap.
  • Develop AI and Gen AI talent as users and SMEs at the platform and System Engineering level.
  • Conduct architectural analyses, benefits analyses, and discoveries related to IT engagements.
  • Work directly with clients, providing engaging presentations, accurate documentation, and leading workshops and interviews.
  • Deliver tailored technology services on an enterprise-wide level while adhering to margin, planning, and SOW requirements.

Requirements

  • 14+ years of experience in Artificial Intelligence and GenAI, with at least 1+ years in GenAI Projects.
  • Deep knowledge of Generative AI, including model selection, data preparation for GenAI training, model fine tuning and Customization, and guardrail implementation.
  • Understanding of the GenAI tooling ecosystem, including Kubernetes, MLops, and AIops tools.
  • Ability to gain customer trust, plan, organize, drive customer workshops, and present findings effectively.
  • Demonstrated capacity to articulate complex concepts, build consensus, and deliver outstanding work products.
  • Familiarity with Nvidia AI tools, including Bright Command Manager, Nemo Framework, and Triton Inference Server.
  • Proficiency in Large Language Models (LLM).
  • Competency using MLOps and AIOps tools such as cnvrg.io, mlfow, and Domino.
  • Expertise in Lean and Iterative Deployment Methodologies.
  • Educational background in Machine Learning is an asset.
  • Certifications in relevant fields are preferred.
  • On-site customer workshops may be required.

View Assessment Process

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