Director - AI Architect

3 weeks ago

India Live Connections Full time

Role: Director Principle Technology Architect

Experience: 15+ yrs

Work Mode: Remote

Budget: 55 lpa includes 10% var


**Finding strong AI Architect profiles with a solid background in Design & development.


Key Responsibilities:

· Design and Oversee AI Architecture: Develop the overall architecture for the LLM from pretraining to supervised fine tuning and RLHF.

· Technical Strategy and Roadmap: Define the technical strategy and create a roadmap for the project, aligning it with organizational goals.

· Technology Selection: Make high-level decisions on technology stack, frameworks, and tools to be used in the development and deployment of the use case, platforms and solutions.

· Integration Management: Oversee the integration of various AI components, including data pipelines, model training environments, and deployment infrastructure.

· Risk Management: Identify potential technical risks in the project and develop strategies to mitigate them.

· Collaboration: Work closely with data scientists, engineers, domain experts, and stakeholders to ensure cohesive development and implementation.

· Innovation and Best Practices: Stay informed about the latest advancements in AI technology and implement best practices to enhance the LLM's capabilities.

· Research and Evaluation: Conduct comprehensive research on existing LLM architectures, including open-source models like GPT, Mistral, DeepSeek, Qwwn and domain-specific variants like FinBERT.


Required Skills:

· Extensive AI/ML Experience: Deep knowledge of artificial intelligence and machine learning concepts, particularly in natural language processing (NLP) and large language models (LLMs).

· Software Architecture Expertise: Strong understanding of software architecture principles, including scalability, modularity, and security.

· Cloud Computing Proficiency: Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and distributed computing environments.

· Data Architecture Knowledge: Familiarity with data management practices, big data technologies, and data pipeline design.

· MLOps Experience: Understanding of MLOps practices for continuous integration, delivery, and monitoring of machine learning models.

· Leadership Skills: Strong leadership abilities to guide technical teams and communicate effectively with non-technical stakeholders.

· Problem-Solving Abilities: Excellent analytical skills to address complex technical challenges and devise innovative solutions.


Interested Candidate please forward your updated resume at

or whats up at


Warm Regards,

Anjana

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