Role : Lead Data Scientist / AI-ML Lead

Location : Hyderabad

Experience : 8+ Years

Mode : Hybrid

Interview : 1st Virtual, 2nd In Person.

Technical Skills Mandatory :

- Python, AI/ML, Azure Open AI, AWS BedRock, Gen AI, Agentic AI, LLM, RAG, MLOps.

Roles and Responsibilities :

- Lead the design, development, and deployment of end-to-end data science and machine learning solutions.

- Strong hands-on experience in Python and data science libraries such as Pandas, NumPy, Scikit-learn, PyTorch, and TensorFlow.

- Design and implement machine learning models for classification, regression, clustering, forecasting, recommendation, and NLP use cases.

- Strong understanding of statistics, probability, hypothesis testing, experimentation, feature engineering, and model evaluation.

- Experience with Generative AI, Large Language Models (LLMs), Prompt Engineering, RAG, embeddings, vector databases, and AI agents.

- Experience building and deploying production-grade AI/ML solutions using cloud platforms such as Azure or AWS.

- Hands-on experience with Azure AI Foundry / Azure OpenAI / Amazon SageMaker or equivalent AI/ML platforms.

- Experience designing data pipelines and ML pipelines for training, validation, deployment, and monitoring.

- Experience with MLOps, including model versioning, experiment tracking, CI/CD, model deployment, monitoring, and model drift detection.

- Strong experience working with SQL and relational databases and familiarity with data warehouses/data lakes.

- Experience with REST APIs, microservices, Docker, and Kubernetes for AI/ML application deployment.

- Implement AI/ML solutions with appropriate security, privacy, responsible AI, and governance controls.

- Optimize models for accuracy, scalability, latency, reliability, and cost.

- Lead technical discussions and mentor Data Scientists, ML Engineers, and junior team members.

Required Skills :

- 8+ years of experience in Data Science / Machine Learning / AI.

- Strong programming experience in Python.

- Strong knowledge of Machine Learning and Deep Learning algorithms.

- Strong understanding of statistics and mathematical foundations of ML.

- Hands-on experience with Generative AI and LLM applications.

- Experience with RAG architectures, embeddings, vector databases, and semantic search.

- Experience with AI Agents / Agentic AI architectures.

- Experience with Azure AI Foundry, Azure OpenAI, AWS SageMaker, or equivalent platforms.

- Strong experience with ML model development, evaluation, deployment, and monitoring.

- Experience with MLOps and ML lifecycle management.

- Strong SQL and data manipulation skills.

- Experience with Git and CI/CD.

- Experience with Docker and Kubernetes is preferred.

- Experience with cloud services such as Azure / AWS.

- Strong understanding of AI security, responsible AI, data privacy, and AI governance.

- Ability to translate business requirements into scalable AI/ML solutions.