Lead Data Scientist

We are seeking a highly skilled Senior/Lead Data Scientist with deep expertise in AI/ML/Gen AI, including Deep Learning, Computer Vision, and NLP. The ideal candidate will bring strong hands-on experience, particularly in building, fine-tuning, and deploying models, and will work directly with customers with minimal supervision.

This role requires someone who can not only lead and execute technical projects but also actively contribute to business development through customer interaction, proposal building, and RFP responses. You will be expected to take ownership of AI project execution and team leadership, while helping Tekdi expand its AI footprint.

Key Responsibilities

Contribute to AI business growth by working on RFPs, proposals, and solutioning activities.

• Lead the team in delivering customer requirements, ensuring quality and timely execution.
  
  

Develop and fine tune advanced AI/ML models using deep learning and generative AI techniques.

• Fine-tune and optimize Large Language Models (LLMs) such as GPT, BERT, T5, and LLaMA.
• Interact directly with customers to understand their business needs and provide AI-driven solutions.
• Work with Deep Learning architectures including CNNs, RNNs, and Transformer-based models.
• Leverage NLP techniques such as summarization, NER, sentiment analysis, and embeddings.
• Implement MLOps pipelines and deploy scalable AI solutions in cloud environments (AWS, GCP, Azure).
• Collaborate with cross-functional teams to integrate AI into business applications.
• Stay updated with AI/ML research and integrate new techniques into projects.
  
  

Required Skills & Qualifications

• Minimum 6 years of experience in AI/ML/Gen AI, with at least 3+ years in Deep Learning/Computer Vision.
• Strong proficiency in Python and popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, Scikit-learn).
• Hands-on experience with LLMs and generative models (e.g., GPT, Stable Diffusion).
• Experience with data preprocessing, feature engineering, and performance evaluation.
• Exposure to containerization and cloud deployment using Docker, Kubernetes.
• Experience with vector databases and RAG-based architectures.
• Ability to lead teams and projects, and work independently with minimal guidance.
• Experience with customer-facing roles, proposals, and solutioning.
  
  

Educational Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Information Technology, or related field.
  
  

Preferred Skills (Good To Have)

• Knowledge of Reinforcement Learning (e.g., RLHF), multi-modal AI, or time-series forecasting.
• Familiarity with Graph Neural Networks (GNNs).
• Exposure to Responsible AI (RAI), AI Ethics, or AutoML platforms.
• Contributions to open-source AI projects or publications in peer-reviewed journals.
  
  

Skills:- Artificial Intelligence (AI) and Machine Learning (ML)