Specialist

We are seeking a highly skilled and experienced Specialist - AI/ML/Gen AI Engineer to join our team in Pune, Maharashtra, India. This role requires a deep understanding of applied machine learning, artificial intelligence, and Generative AI, with a proven track record in developing and deploying sophisticated AI solutions.

Key responsibilities include leading the complete AI/ML pipeline from data ingestion and exploration to model deployment and monitoring. You will be responsible for the end-to-end delivery of data acquisition, complex transformation and orchestration pipelines, AI/ML engineering, and front-end visualization. This involves designing, building, and deploying machine learning models (classification, regression, deep learning) for real-world business applications.

You will leverage advanced Generative AI techniques to solve problems in content generation, summarization, text classification, and intelligent automation. This includes fine-tuning, optimizing, and deploying Large Language Models (LLMs) such as GPT, BERT, and LLaMA for custom use cases using techniques like transfer learning and LoRA. Developing prompt engineering frameworks and reusable GenAI patterns to accelerate model development is crucial. You will also build Retrieval-Augmented Generation (RAG) pipelines for domain-specific applications using vector databases and embedding models, and integrate GenAI APIs and services (e.g., OpenAI, Azure OpenAI, Hugging Face, LangChain) into internal platforms and products.

Ensuring responsible AI practices is paramount. You will implement guardrails, safety filters, and evaluation metrics for GenAI models. Advanced text mining, semantic search, document clustering, and knowledge graph generation using GenAI are also key aspects of this role. Driving GenAI model governance, including versioning, bias/fairness assessments, and monitoring drift in deployed systems, will be essential. Collaboration with product and engineering teams to deliver GenAI-powered features in production systems is expected. You will also mentor junior AI/ML team members and foster the adoption of GenAI techniques across the organization.

The role demands strong foundational knowledge in statistics, probability, and mathematics, with proven experience in feature engineering, model tuning, and a solid understanding of data structures and algorithms. Expertise in classification/regression techniques, ensemble methods, and deep learning architectures, including transformer models (e.g., BERT, GPT), RNNs, and CNNs, is required. Proficiency in programming languages like Python, with experience using ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost), is essential. Solid experience with GenAI tools and frameworks (e.g., OpenAI, LangChain, HuggingFace Transformers) is also a must.

You will design and implement robust ML models, apply advanced statistical techniques, and optimize model performance through hyperparameter tuning and evaluation metrics analysis. Deploying models to production environments using best practices in MLOps and CI/CD pipelines is a core function. Experience with state-of-the-art architectures including Transformers, LSTM, and CNNs for deep learning use cases (e.g., NLP, computer vision) is important. Translating complex technical concepts into clear business insights and recommendations is expected. You will lead the end-to-end ML lifecycle: data exploration, feature engineering, model selection, training, evaluation, deployment, and monitoring.

Experience with MLOps, CI/CD, feature engineering, dimensional modeling, and data engineering will be essential for success. Familiarity with MLOps principles, version control (Git), and model monitoring tools is required. Experience with cloud platforms (e.g., Azure, AWS, GCP) for scalable AI/ML deployment and CI/CD pipelines in ML model delivery is beneficial. Experience working with large-scale datasets and distributed computing frameworks like Spark is a plus. Good understanding of data engineering practices, ETL pipelines, and dimensional modeling is also valuable. Working knowledge of SQL, Snowflake, and other cloud data warehouses is an added advantage.

Excellent communication and stakeholder management skills are required. This role offers a fantastic opportunity to work with cutting-edge AI and GenAI technologies in a dynamic environment.