Tech Lead - AI / ML

As an AI/ML Lead at our company, you will be responsible for designing, developing, and deploying advanced machine learning and natural language processing (NLP) solutions. Your role will involve leading the end-to-end lifecycle of AI/ML projects, including model architecture, fine-tuning private large language models (LLMs), and ensuring production-grade deployment and optimization. This is a customer-facing leadership position that requires a combination of strong technical depth and the ability to translate AI capabilities into tangible business impact. Key Responsibilities: - Lead the design, development, and implementation of AI/ML solutions, focusing on NLP, multi-class/multi-label text classification, and LLM-based applications. - Architect and fine-tune private LLMs (e.g., LLaMA, Gemma) and integrate them with public LLM APIs (e.g., OpenAI, Anthropic Claude). - Drive the adoption of Retrieval-Augmented Generation (RAG) and vector databases (e.g., Pinecone, ChromaDB) for intelligent knowledge systems. - Provide technical leadership and mentorship to a team of ML engineers and data scientists, ensuring best practices in model development, MLOps, and scalability. - Oversee ML lifecycle management, including data preprocessing, model training, evaluation, tracking (MLFlow/KubeFlow), and deployment to production. - Collaborate with cross-functional teams (data engineering, product, architecture, and customer teams) to deliver high-impact AI solutions aligned with business goals. - Integrate explainability and interpretability frameworks (e.g., Captum, SHAP, and LIME) to ensure transparency and compliance in AI models. - Utilize platforms like Databricks for scalable model training, monitoring, and continuous improvement. - Represent AI/ML initiatives in customer discussions, solution presentations, and technical reviews, articulating the business value and technical strategy. Qualifications Required: - 5+ years of experience in AI/ML solution design and implementation, with a strong emphasis on NLP and deep learning. - Proven hands-on experience in fine-tuning and deploying private LLMs (e.g., LLaMA, Gemma) for custom use cases. - Expertise in PyTorch, Hugging Face, LangChain, LangGraph, and Haystack frameworks. - Proficiency in ML orchestration tools like MLFlow, KubeFlow, and Databricks for model lifecycle management. - Strong understanding of vector databases (Pinecone, ChromaDB, FAISS) and RAG pipelines. - Experience integrating AI explainability frameworks for model transparency. - Knowledge of multi-modal AI (text-image/audio integration) is an advantage. - Excellent leadership, communication, and stakeholder management skills with the ability to guide both technical and non-technical audiences. In addition to the above, exposure to cloud platforms (Azure, AWS, GCP) for scalable AI deployment, experience in MLOps automation and CI/CD pipelines for ML workflows, knowledge of multi-agent systems or AI orchestration frameworks, and contributions to open-source AI/ML projects or research publications are considered advantageous for this role. As an AI/ML Lead at our company, you will be responsible for designing, developing, and deploying advanced machine learning and natural language processing (NLP) solutions. Your role will involve leading the end-to-end lifecycle of AI/ML projects, including model architecture, fine-tuning private large language models (LLMs), and ensuring production-grade deployment and optimization. This is a customer-facing leadership position that requires a combination of strong technical depth and the ability to translate AI capabilities into tangible business impact. Key Responsibilities: - Lead the design, development, and implementation of AI/ML solutions, focusing on NLP, multi-class/multi-label text classification, and LLM-based applications. - Architect and fine-tune private LLMs (e.g., LLaMA, Gemma) and integrate them with public LLM APIs (e.g., OpenAI, Anthropic Claude). - Drive the adoption of Retrieval-Augmented Generation (RAG) and vector databases (e.g., Pinecone, ChromaDB) for intelligent knowledge systems. - Provide technical leadership and mentorship to a team of ML engineers and data scientists, ensuring best practices in model development, MLOps, and scalability. - Oversee ML lifecycle management, including data preprocessing, model training, evaluation, tracking (MLFlow/KubeFlow), and deployment to production. - Collaborate with cross-functional teams (data engineering, product, architecture, and customer teams) to deliver high-impact AI solutions aligned with business goals. - Integrate explainability and interpretability frameworks (e.g., Captum, SHAP, and LIME) to ensure transparency and compliance in AI models. - Utilize platforms like Databricks for scalable model training, monitoring, and continuous improvement. - Represent AI/ML initiatives in customer discussions, solution presentations, and technical reviews, articulating the busines