Data Architect

1 day ago

Anantapur, Andhra Pradesh, India beBeeData Full time ₹ 1,80,00,000 - ₹ 2,40,00,000
Job Title: Data Architect

Summary: Drive the development and deployment of large-scale AI systems, ensuring alignment with organizational goals and strategic initiatives.

Key Responsibilities:

  • Design and deploy advanced AI solutions across multiple domains, leveraging deep learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
  • Lead the architecture and implementation of state-of-the-art Generative AI models, including LLMs, GANs, diffusion models, and multimodal systems.
  • Oversee the development of scalable ML pipelines, ensuring robustness, reliability, and efficiency in cloud and edge deployments.
  • Provide technical leadership in MLOps, deployment strategies, and governance for AI models, collaborating with executive leadership and domain experts to shape AI-driven innovation.
  • Evaluate emerging research and technologies in AI/ML, recommending adoption strategies for enterprise-scale impact.
  • Mentor and grow data scientists, ML engineers, and research teams, fostering a culture of collaboration and knowledge-sharing.

Required Skills & Qualifications:

  • Education: Master's or PhD in Computer Science, Data Science, AI/ML, or related field.
  • Experience: 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 industries, including manufacturing, healthcare, finance, logistics, and more.
  • Strong expertise in deep learning frameworks, 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, leveraging tools like AWS, Azure, GCP, and Kubernetes.
  • Experience with MLOps (MLflow, Kubeflow, Docker, CI/CD) and responsible AI practices.

Preferred Skills:

  • 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.

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