Ai Technical Architect

2 weeks ago

Coimbatore, India Whatjobs IN C2 Full time

Role - AI Technical Architect Experience - 15+ years Budget - Up to 55 LPA including 15% variables Work Mode - Remote Required Notice Period - Immediate to 30 days 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. 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. To apply, connect with Abhishek via or WhatsApp on

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