About the Role
We are looking for a Data Scientist with 6+ years of experience in AI/ML and Generative AI to build scalable, enterprise-grade intelligent solutions.
The ideal candidate will have hands-on experience in Deep Learning, NLP, Large Language Models (LLMs), AI Agents, RAG pipelines, and cloud-native AI deployments. You will work closely with cross-functional teams to design, develop, and deploy innovative AI applications using modern frameworks and technologies.
Experience: 6+ Years
Employment Type: Full-Time
Location: Bengaluru (Onsite)
Key Responsibilities
- Design, develop, and deploy AI/ML and Generative AI solutions for enterprise applications.
- Build and optimize NLP models, RAG pipelines, and agentic AI workflows.
- Develop AI agents using frameworks such as LangGraph and implement prompt engineering workflows for LLMs including GPT, Claude, and LLaMA.
- Work with large-scale image and video datasets, including data preprocessing and augmentation techniques.
- Build and fine-tune deep learning models using TensorFlow and PyTorch.
- Collaborate with cross-functional teams to develop scalable and production-ready AI solutions.
- Implement MLOps best practices, including model versioning, CI/CD pipelines, and automated model deployment.
- Work with Databricks, Azure cloud services, and UNIX/Linux environments to build and deploy AI applications.
Required Skills & Qualifications
- 6+ years of experience in Data Science or related AI/ML domains.
- Strong proficiency in Python and modern software development practices.
- Hands-on experience with TensorFlow and/or PyTorch.
- Strong understanding of NLP techniques, Transformer architectures, RNNs, Transfer Learning, and Vision Transformer (ViT) models.
- Experience building Generative AI applications, including RAG pipelines and agentic workflows.
- Hands-on experience with AI agent frameworks such as LangGraph.
- Experience designing and optimizing prompt engineering workflows for LLMs.
- Strong expertise in Databricks and the Azure cloud ecosystem.
- Experience with MLOps practices, including CI/CD pipelines, model versioning, and automated deployments.
- Proficiency working in UNIX/Linux environments and scripting tools.
Preferred Skills
- Exposure to Convolutional Neural Networks (CNNs) and Reinforcement Learning.
- Knowledge of enterprise AI security, compliance, and governance practices.
- Strong analytical, communication, and collaboration skills with the ability to work effectively in cross-functional teams.
