Overview

We're looking for a Lead AI Scientist This role is Office Based, Hyderabad Office

Responsibilities

• Design and develop LLM, Generative AI, RAG, NLP, recommendation, personalization, and agentic AI solutions.
• Research and evaluate state-of-the-art AI/ML techniques and determine their applicability to business problems.
• Develop and fine-tune foundation models, domain-specific models, embedding models, and task-specific models.
• Design training, fine-tuning, evaluation, and inference pipelines for AI models.
• Apply techniques such as transformer architectures, LLM fine-tuning, RAG, embeddings, vector search, deep learning, reinforcement learning, contextual bandits, and information retrieval.
• Develop experimentation frameworks and establish metrics for model quality, relevance, accuracy, robustness, latency, and cost.
• Investigate model behavior through experimentation, error analysis, ablation studies, and statistical analysis.
• Build prototypes and proof-of-concepts and transition successful approaches into production systems.
• Collaborate with Software Engineering, Product, Data Engineering, and Platform teams to productionize AI solutions.
• Optimize models and AI systems for accuracy, scalability, latency, memory, and inference cost.
• Design and implement model evaluation frameworks, including automated, human, and LLM-based evaluation.
• Stay current with advances in AI research and translate relevant research into practical solutions.
• Publish internal research, technical documentation, patents, or external research papers where appropriate.
• Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related technical field.
• 7+ years of experience in AI/ML, Data Science, or a closely related field.
• Strong understanding of machine learning and deep learning fundamentals.
• Strong hands-on experience with Python and modern ML frameworks such as PyTorch or TensorFlow.
• Experience developing and deploying machine learning models at scale.
• Strong experience with one or more of Generative AI/LLMs, NLP, recommendation systems, information retrieval, deep learning, reinforcement learning, or computer vision.
• Experience with transformer architectures and modern foundation models.
• Experience with model fine-tuning, embeddings, vector databases, RAG, and LLM evaluation.
• Strong understanding of experimentation, statistical modeling, model evaluation, and hypothesis testing.
• Experience working with large-scale datasets and distributed computing frameworks such as Spark.
• Strong analytical, communication, and problem-solving skills.
• Experience with foundation models such as Llama, Mistral, Gemini, or comparable models.
• Experience with Hugging Face, LangChain/LangGraph, FAISS, Milvus, Weaviate, or similar AI technologies.
• Experience with model optimization techniques such as quantization, distillation, pruning, and parameter-efficient fine-tuning (PEFT/LoRA).
• Experience designing production-grade AI platforms and services.
• Experience with Docker, Kubernetes, cloud AI/ML platforms, and MLOps.
• Experience with MLflow or similar experiment and model management platforms.