AI Strategist

1 day ago

Rajkot, Gujarat, India beBeeArtificialIntelligence Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

We are seeking an accomplished AI Strategist to lead the conception, design, and deployment of sophisticated Machine Learning, Deep Learning, and Generative AI systems.

The ideal candidate will have a strong background in AI/ML strategy, with experience in architecting and implementing state-of-the-art Generative AI solutions, including Large Language Models (LLMs), Vision Language Models (VLMs), diffusion models, and multimodal systems.

Responsibilities include overseeing the development of scalable Machine Learning pipelines, ensuring robustness, reliability, and efficiency, as well as providing technical leadership in MLOps, deployment strategies, and governance for AI models across edge and cloud.

The successful candidate will collaborate with executive leadership, product managers, and domain experts to shape AI-driven innovation, evaluate emerging research and technologies in AI/ML, and recommend adoption strategies for enterprise-scale impact.

Additionally, the AI Strategist will mentor, coach, and grow data scientists, ML engineers, and research teams, ensuring the organization remains at the forefront of AI/ML advancements.

Required Skills & Qualifications:

  • Masters/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 (manufacturing, healthcare, finance, logistics, etc.)
  • 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 (AWS, Azure, GCP) and hybrid/edge deployments
  • Experience with MLOps (MLflow, Kubeflow, Docker, Kubernetes, 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
  • Global experience working across geographies and diverse teams

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