Senior Data Science Manager

Job description

We are seeking a seasoned AI professional with a strong background in **Generative AI, Deep Learning, and Large Language Models (LLMs)**. As a senior leader, you will play a pivotal role in designing, developing, and scaling cutting-edge generative AI solutions that transform how we interact with data, customers, and products. This is a highly strategic and technical role, ideal for someone who thrives at the intersection of research, engineering, and leadership. **Key Responsibilities:** - Lead the design and development of generative AI solutions, including **LLMs, diffusion models, GANs, and transformers**. - Oversee the lifecycle of AI projectsfrom problem framing, data acquisition, model development, to deployment and monitoring. - Mentor and lead a team of ML/AI engineers and researchers; provide technical guidance and architectural vision. - Collaborate with cross-functional teams (Product, Engineering, Data Science, Design) to embed AI capabilities into business-critical products. - Evaluate and implement state-of-the-art open-source or proprietary models (e.g., GPT, Claude, LLaMA, DALL•E, Stable Diffusion). - Drive model fine-tuning, prompt engineering, RLHF (Reinforcement Learning with Human Feedback), and scalable training strategies. - Ensure ethical and responsible AI development aligned with industry best practices. **Required Qualifications:** - 12–16 years of experience in AI/ML, with at least 3–5 years in **Generative AI or LLM-based development**. - Advanced degree (PhD or Master’s) in Computer Science, Machine Learning, Mathematics, or related field. - Strong programming skills in **Python**, and experience with **ML/DL frameworks** (e.g., PyTorch, TensorFlow, Hugging Face). - Proven experience working with LLMs (e.g., GPT, BERT, T5, LLaMA) or vision-language models. - Deep understanding of deep learning architectures: Transformers, Attention Mechanisms, GANs, VAEs, etc. - Track record of deploying AI models in production environments (MLOps experience is a plus). - Familiarity with cloud platforms (AWS, Azure, GCP) and scalable model training/inference pipelines. **Preferred Qualifications:** - Experience leading AI research initiatives or contributing to publications. - Hands-on with vector databases, embedding models, retrieval-augmented generation (RAG). - Strong understanding of AI ethics, fairness, interpretability, and safety in generative models. - Prior experience in domains such as healthcare, fintech, enterprise SaaS, or creative industries is a plus. **Why Join Us?** - Work on cutting-edge generative AI applications with real-world impact. - Be part of a fast-growing, innovation- driven AI team. - Competitive compensation, flexible work environment, and opportunities for professional growth.