Data Science Leader

1 day ago

Kozhikode, Kerala, India beBeeDataScientist Full time ₹ 1,80,00,000 - ₹ 2,00,00,000
Lead Data Science Professional

Strategic AI/ML Leadership Role

We are seeking a seasoned data science leader to drive our organization's AI strategy, designing and architecting large-scale machine learning, deep learning, and generative AI systems. The ideal candidate will lead the development of robust, scalable, and efficient AI solutions in alignment with organizational goals.

Key Responsibilities:

  • Develop and deploy cutting-edge generative AI solutions including language models, vision models, diffusion models, and multimodal systems.
  • Create scalable machine learning pipelines ensuring high performance, reliability, and efficiency.
  • Provide technical leadership in MLOps, deployment strategies, and governance for AI models across edge and cloud environments.
  • Collaborate with executive leadership, product managers, and domain experts to shape AI-driven innovation and strategic initiatives.
  • Evaluate emerging research and technologies in AI/ML and recommend adoption strategies for enterprise-scale impact.
  • Mentor, coach, and grow data science teams, ML engineers, and research professionals.

Requirements:

  • Master's or PhD in Computer Science, Data Science, AI/ML, or related field.
  • 10+ years of experience in machine learning and deep learning with at least 3+ years in leadership roles.
  • Proven track record in deploying AI solutions at scale across multiple domains.
  • Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
  • Hands-on experience with generative AI models (LLMs, GANs, diffusion models, transformers, VLMs).
  • Strong knowledge of model fine-tuning, transfer learning, RAG pipelines, and vector databases.
  • Deep understanding of distributed systems, model optimization, and high-performance computing for AI workloads.
  • Proven ability to architect AI solutions across cloud and hybrid/edge deployments.
  • Experience with MLOps (MLflow, Kubeflow, Docker, Kubernetes, CI/CD) and responsible AI practices.

Preferred Qualifications:

  • Experience in Industry 4.0 use cases such as digital twins, predictive maintenance, robotics, and computer vision in industrial environments.
  • Familiarity with Agentic AI frameworks, Model Context Protocol (MCP), and knowledge graph-based reasoning.
  • Understanding of reinforcement learning, edge AI, and federated learning.
  • Global experience working across geographies and diverse teams.

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