Data Scientist II

Overview

Build and productionize enterprise-grade AI and generative AI solutions using software engineering, model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps.

What you'll do

• Design and maintain scalable AI/ML applications, APIs, and reusable components.
• Fine-tune and evaluate foundation models using LoRA, QLoRA, PEFT, and supervised fine-tuning.
• Build RAG solutions, embedding workflows, vector-search applications, and AI agents.
• Create ML pipelines for preparation, training, evaluation, deployment, monitoring, and retraining.
• Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving.
• Implement CI/CD, automated testing, observability, model monitoring, and production support.
• Partner with data science, engineering, product, security, privacy, and governance teams.

What you'll need

• 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field.
• Strong Python, SQL, object-oriented programming, data structures, API development, testing, Git, and software design skills.
• Hands-on experience with Databricks, Spark/PySpark, MLflow, model registries, and production ML workflows.
• Practical AWS experience with secure cloud architecture, containers, monitoring, and access controls.
• Experience with PyTorch, Hugging Face, scikit-learn, FastAPI/Flask, Docker, Kubernetes, and CI/CD.
• Understanding of model performance, latency, scalability, cost optimization, data quality, and responsible AI controls.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related STEM field.

Nice to have

• Experience with enterprise generative AI.
• Experience with financial services or payments data.
• Experience with LangChain/LangGraph.
• Experience building production-grade RAG or agentic AI systems.

Details

• Location: Gurgaon, Haryana, India.