Required Skills :

- Experience in AI/ML engineering, with at least 5+ years delivering Generative AI models into production.

- Bachelors/Masters/PhD in Computer Science, Mathematics, Statistics, or related field from a top-tier institution (IITs/NITs/BITs etc.).

- Strong applied programming skills in Python, SQL, R and experience with data science libraries such as NumPy, Pandas, MatLab, scikit-learn.

- Proven experience with deep learning frameworks : PyTorch, TensorFlow, Keras, MXNet, Caffe.

- Familiarity with NLP and ML libraries : Transformers, SparkNLP, Gensim, SpaCy, NLTK, Hugging Face.

- Experience building and fine-tuning LLMs and integrating them with orchestration frameworks (LangChain, LlamaIndex).

- Expertise with vector databases (Pinecone, FAISS, Weaviate, Milvus) and knowledge of embedding retrieval patterns.

- Cloud-native ML experience (AWS Sagemaker, GCP Vertex AI, Azure ML) and containerization (Docker, Kubernetes).

- Applied knowledge of classical ML algorithms (SVM, Decision Trees, Random Forests, regression, clustering) alongside modern DL/GenAI approaches.

- Strong knowledge of CI/CD for ML, model observability (MLflow, Weights & Biases, LangSmith), and governance frameworks.

- Excellent problem-solving skills, communication, and ability to lead technical teams.