AI Technical Architect

• Collaborate with software engineers, business stake holders and/or domain experts to translate business requirements into product features, tools, projects, AI/ML, NLP/NLU and deep learning solutions.
• Develop, implement, and deploy AI/ML solutions.
• Preprocess and analyze large datasets to identify patterns, trends, and insights.
• Evaluate, validate, and optimize AI/ML models to ensure their accuracy, efficiency, and generalizability.
• Deploy applications and AI/ML model into cloud environment such as AWS/Azure/Google Cloud Platform etc.
• Monitor and maintain the performance of AI/ML models in production environments, identifying opportunities for improvement and updating models as needed.
• Document AI/ML model development processes, results, and lessons learned to facilitate knowledge sharing and continuous improvement.

We're seeking a senior AI/ML Engineer with minimum 9-10 yrs experience who can serve as a Technical Architect-owning end-to-end design and delivery of machine learning solutions. This role blends hands-on model development, ML platform engineering, and architectural governance to build scalable, secure, and cost-effective AI systems that power high-impact business use cases., * Bachelor's or master's degree in Computer Science, Data Science, Engineering, or a related field.

• Experience on Agentic AI/ Frameworks
• Strong programming skills in languages such as Python, SQL/NoSQL etc.
• Build analytical approach based on business requirements, then develop, train, and deploy machine learning models and AI algorithms
• Exposure to GEN AI models such as OpenAI, Google Gemini, Runway ML etc.
• Experience in developing and deploying AI/ML and deep learning solutions with libraries and frameworks, such as TensorFlow, PyTorch, Scikit-learn, OpenCV and/or Keras.
• Knowledge of math, probability, and statistics.
• Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms.
• Exposure in developing API using Flask/Django.
• Good experience in cloud infrastructure such as AWS, Azure or Google Cloud Platform
• Exposure to Gen AI, Vector DB/Embeddings, LLM (Large language Model)