AI/ML Team Lead

Job Purpose

To lead the design, development, and deployment of advanced AI/ML and Generative AI solutions, driving innovation and business value across the organization. This role serves as the technical and strategic leader responsible for shaping AI initiatives, ensuring scalable architecture, and aligning solutions with business objectives. The AI/ML/Gen AI Lead will also manage cross-functional collaboration, effectively communicating with stakeholders to translate complex technical concepts into actionable insights and drive adoption of AI technologies. Must have experience both POC and with Production grade solutions

Key Responsibilities

Generative AI Leadership

Architect and deploy GenAI solutions such as:
Chatbots and conversational agentsIntelligent document processingCode generation and copilotsContent summarization, personalization, or generationCustomize and fine-tune foundation models (e.g., GPT, LLaMA, Claude, Mistral) for domain-specific use cases.Drive evaluation and integration of GenAI frameworks and tooling (e.g., LangChain, Semantic Kernel, LlamaIndex, Transformers).Implement prompt engineering and retrieval-augmented generation (RAG) pipelines at scale.

Technical Strategy & Execution

Define and execute the Generative AI roadmap aligned with business goals.
Collaborate with product, engineering, and business stakeholders to identify and prioritize GenAI use cases.Lead POCs and pilots to validate ideas before full-scale implementation.Ensure robust, secure, and ethical deployment of GenAI systems, including governance and monitoring.

Team Leadership & Mentorship

Lead, mentor, and grow a team of AI/ML engineers and researchers.
Establish best practices in model development, experimentation, and deployment.Foster a culture of continuous innovation and learning in GenAI.

Platform & Infrastructure (Supporting Azure)

Deploy and operationalize models using cloud platforms, ideally Azure AI services (OpenAI on Azure, Azure ML, Azure Cognitive Search).
Manage GenAI infrastructure (e.g., vector databases, inference endpoints, GPUs) for performance and cost-efficiency.Utilize MLOps practices for model lifecycle management and reproducibility.

Experience Required

• 8+ years of experience in AI/ML, with at least 2+ years in GenAI-specific roles.
• Proven experience with foundation models (e.g., GPT-4, Claude, LLaMA) and relevant toolsets.
• Proficiency in Python and AI/ML libraries (e.g., PyTorch, Transformers, Hugging Face).
• Strong understanding of prompt engineering, RAG, LLMOps, and LLM fine-tuning.
• Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Azure AI Search).
• Familiarity with enterprise AI integration (APIs, plugins, cloud deployment).

Preferred Qualifications

Bachelors or Master’s degree in Computer Science, Machine Learning, AI, or a related field (PhD preferred).