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Gen AI Manager / AI Project Manager
Gen AI Manager / AI Project Manager
Merkle Technologies is seeking a Gen AI Manager / AI Project Manager with 14+ years of experience in AI and GenAI. This role involves leading GenAI projects, influencing technology roadmaps, and providing consultancy while working closely with clients. The manager will also be responsible for developing AI and Gen AI talent within the organization.
About the role
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.