Jobopening For AI/Ml Lead in our organisation

Role & responsibilities

Required Skills & Experience

• 68 years of overall software/data engineering experience with minimum 3 years in AI/ML roles.
• Strong hands-on experience in Python and ML frameworks (Scikit-learn, TensorFlow, PyTorch).
• Solid experience in NLP, LLMs, embeddings, vector databases, and prompt engineering.
• Proven experience designing and deploying RAG frameworks and GenAI applications.
• Experience building and exposing ML models via APIs (FastAPI / Flask).
• Hands-on experience with

  cloud-based AI platforms

  (Azure ML, AWS SageMaker, GCP Vertex AI).
• Ability to review code, mentor team members, and enforce engineering best practices.
• Strong analytical, problem-solving, and communication skills.
• Familiarity with Docker containers, container orchestration (Kubernetes), and CI/CD pipelines.
• Fair understanding of ML lifecycle management and MLOps tools (MLflow, Airflow, Kubeflow, etc.).
• Solid understanding of algorithms, data structures, and model evaluation techniques.
• Strong problem-solving skills and the ability to explain complex concepts clearly.

Key Responsibilities

• Lead the end-to-end design and implementation of AI/ML solutions, from problem definition to production deployment.
• Provide technical leadership and guidance to AI/ML engineers and data scientists.
• Architect scalable AI implementation including Cloud based solutions and feature engineering.
• Design and implement Generative AI solutions such as chatbots, assistants, and RAG-based architectures.
• Review model performance, ensure continuous improvement, and handle model drift and retraining strategies.
• Collaborate with data engineering, DevOps, and cloud teams
• Engage with stakeholders to understand requirements, define AI strategy, and set realistic delivery timelines.
• Ensure responsible AI practices including security, governance, privacy, and explainability.
• Evaluate emerging AI technologies and frameworks and recommend adoption where appropriate.
• Own technical documentation, architecture diagrams, and solution design artifacts.