Senior AI Scientist

Cornerstone; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Cornerstone in Hyderabad seeks a Senior AI Scientist to lead the research, development, and deployment of advanced AI/ML solutions across the organization. The role focuses on Generative AI, LLMs, NLP, recommendation systems, and agentic AI to solve complex business problems.

You will take AI ideas from research to production, collaborating with Software Engineering, Product, Data Engineering, and Platform teams to optimize for accuracy, latency, and cost, while publishing internal research when

Qualifications

• Master's or PhD in Computer Science, AI, ML, or related field.
• 3–5 years of experience in AI/ML, Data Science, or related field.
• Strong understanding of ML and DL fundamentals.
• Hands-on Python with PyTorch or TensorFlow.
• Experience deploying ML models at scale.
• Experience with Generative AI/LLMs, NLP, or related areas.
• Experience with transformer architectures and foundation models.
• Experience with embeddings, vector databases, RAG, and LLM evaluation.
• Strong analytical and communication skills.

Responsibilities

• Design and develop LLM, Generative AI, RAG, NLP, recommender, personalization, and agentic AI solutions.
• Research and evaluate state-of-the-art AI/ML techniques for business problems.
• Develop and fine-tune foundation models, embeddings, and task-specific models.
• Design training, fine-tuning, evaluation, and inference pipelines for AI models.
• Apply transformers, LLM fine-tuning, RAG, embeddings, vector search, DL, RL, and IR techniques.
• Build experimentation frameworks and metrics for model quality and cost.
• Investigate model behavior via experiments, ablations, and stats.
• Build prototypes and transition approaches into production systems.
• Collaborate with SWE, Product, Data Eng, and Platform teams to productionize AI solutions.
• Optimize models for accuracy, latency, memory, and cost.
• Design model evaluation frameworks including automated and human evaluation.
• Stay current with AI research and translate to practical solutions.
• Publish internal research or patents where appropriate.

Skills

Python

PyTorch

TensorFlow

LLMs

NLP

Reinforcement Learning

Distributed Computing (Spark)

Model Deployment

MLOps

Education

Master's or PhD in Computer Science/AI/ML/Statistics/Math

Tools

Docker

Kubernetes

MLflow

Hugging Face

FAISS

LangChain

Spark

Job description

Role Overview

We are looking for a Senior AI Scientist to drive the research, development, and deployment of advanced Artificial Intelligence and Machine Learning solutions across the organization. The role will focus on solving complex business and product problems using modern AI techniques, including Generative AI, Large Language Models (LLMs), NLP, recommendation systems, deep learning, reinforcement learning, and agentic AI.

The ideal candidate combines strong scientific thinking with hands-on engineering capabilities and can take AI ideas from research and experimentation through production deployment and continuous optimization.

In This Role You Will

• 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.

You\'ve Got What It Takes If You Have

• Master\'s or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related technical field.


• 3 to 5 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.

Extra Dose of Awesome If You Have

• 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.


• Experience with AI evaluation frameworks and LLM-as-a-Judge approaches.


• Research publications, patents, or contributions to open-source AI projects.

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