AI Leader

6 hours ago

Kanpur, Uttar Pradesh, India beBeeData Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Role: Lead Data Scientist

As a key member of the AI and Machine Learning team, you will play a critical role in driving innovation and developing cutting-edge machine learning solutions.

This position requires a professional with expertise in NLP, Large Language Models (LLMs), Generative AI, and MLOps who can lead the development of scalable AI-driven solutions and provide strategic direction to a team of data scientists.

The ideal candidate should possess deep knowledge in AI/ML strategies, model deployment, and AI governance as well as experience with designing and developing complex machine learning models.

Responsibilities:
  • Define and Drive AI/ML Strategy
  • Lead research, design, and development of cutting-edge machine learning models, including LLMs, GANs, VAEs, Transformers, CNNs, and RNNs.
  • Establish best practices for data pipelines, feature engineering, model deployment, and AI governance.
  • Evaluate emerging AI/ML technologies and recommend their adoption where beneficial.
  • Architect and implement Generative AI solutions with a focus on improving conversational AI experiences.
  • Optimize LLMs (GPT, BERT, T5, etc.) for various business applications, including prompt engineering, fine-tuning, and model interpretability.
  • Work on text generation, semantic search, intent recognition, and AI-driven recommendation systems.
  • Oversee end-to-end model lifecycle, from data collection and preprocessing to model deployment and monitoring.
  • Implement MLOps best practices to streamline model retraining, CI/CD for ML pipelines, and productionization.
  • Optimize models using hyperparameter tuning techniques such as grid search, Bayesian optimization, and neural architecture search.
  • Lead and Mentor Team Members
  • Conduct code reviews, design discussions, and knowledge-sharing sessions.
  • Guide junior team members on best practices in data science, deep learning, and software engineering.
  • Partner with engineering, product management, and business stakeholders to integrate AI solutions into production.

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