Lead Data Scientist / AI Solution Architect

Role Overview:

Lead Data Scientist / AI Solution Architect

Key Responsibilities:

• Architect and implement end-to-end AI/ML solutions using

  Azure AI/ML services

• Lead the design and development of

  LLMOps pipelines

  for deploying and managing large language models (LLMs)
• Work with containerized deployments using

  Docker

  and orchestration tools like

  Kubernetes

• Integrate and fine-tune

  Generative AI models

  for various real-world applications (text, vision, conversation, etc.)
• Collaborate with data engineers, product teams, and business stakeholders to deliver scalable AI systems
• Drive model monitoring, versioning, and responsible AI practices
• Document technical architecture, decision-making, and knowledge transfer

Required Skills & Qualifications:

• 5 to 7 years of experience in

  Data Science / AI / ML solution development

• Strong hands-on experience with

  Azure AI services

  (ML Studio, Azure OpenAI, AI Foundry etc.)
• Experience working with

  LLMs

  , prompt engineering, and fine-tuning techniques
• Proven experience with

  containerized environments

  (Docker, Kubernetes)
• Strong programming skills in

  Python

  with relevant ML/AI libraries (TensorFlow, PyTorch, Transformers, etc.)
• Solid understanding of

  LLMOps/MLOps

  lifecycle and best practices
• Excellent communication, stakeholder management, and team collaboration skills

Must Have:

• Hands-On

  LangChain, Hugging Face APIs, or Azure OpenAI APIs

• Strong knowledge of Azure Cognitive Services, Machine Learning Studio, Azure AI Search, AI Foundry
• Strong Knowledge of basic hygiene principles Git, Clean Code, Unit Testing, Jira, DevOps etc.

Good to Have:

• Experience with Databricks
• Familiarity with Azure

  CI/CD pipelines

• Prior experience working in a

  startup or fast-paced product environmentRole & responsibilities