AI / ML / NLP Architect

7 hours ago

India Techwise Digital Full time ₹ 12,00,000 - ₹ 36,00,000 per year

We are looking for a highly experienced AI/ML/NLP Architect to lead the design, development, and implementation of advanced machine learning and natural language processing solutions. The ideal candidate will have strong hands-on expertise in Python, deep knowledge of modern AI frameworks, and the ability to architect scalable AI systems that solve complex business problems.

Key Responsibilities

  • Lead end-to-end architecture and solution design for AI, ML, and NLP initiatives.
  • Develop scalable, production-grade machine learning and NLP models using Python.
  • Drive the adoption of modern AI technologies, frameworks, and best practices across teams.
  • Collaborate with cross-functional teams to translate business requirements into technical solutions.
  • Design and implement data pipelines, feature engineering workflows, and model deployment strategies.
  • Evaluate new AI/ML tools, libraries, and platforms to determine feasibility and potential adoption.
  • Ensure model performance, reliability, explainability, and compliance with responsible AI standards.
  • Review code, provide technical leadership, and mentor junior engineers.
  • Work closely with DevOps/MLOps teams to operationalize and continuously improve ML models.

Required Skills & Experience

  • 12+ years of experience in AI, ML, NLP, or Data Science, with at least 4–5 years in an architect role.
  • Strong hands-on expertise in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, spaCy, Hugging Face Transformers, etc.
  • Deep understanding of NLP techniques including LLMs, embeddings, RAG architectures, text classification, NER, summarization, and conversational AI.
  • Proven experience designing and deploying end-to-end ML pipelines in production.
  • Strong knowledge of cloud platforms (AWS/Azure/GCP) and MLOps tools (SageMaker, MLflow, Kubeflow, Docker, Kubernetes).
  • Experience with vector databases, feature stores, and modern data engineering frameworks.
  • Solid understanding of data structures, algorithms, distributed systems, and software architecture.
  • Strong communication and stakeholder management skills.

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