Hybrid Data Scientist – Data Science, Gen AI Engineer

at EXL

• Job title: Data Scientist – Data Science, Gen AI Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Docker, Google Cloud Platform, Kubernetes, Python, PyTorch, React, Tensorflow
• Location requirements: Hybrid, Pune, India

About the role

• Data Scientist role designing and deploying scalable AI systems for multi-user applications. Collaborating with cross-functional teams using advanced tools and frameworks in AI.

Responsibilities

• Lead the architecture, development, and deployment of scalable machine learning systems, focusing on real-time inference for LLMs serving multiple concurrent users.
• Optimize inference pipelines using high-performance frameworks like vLLM, Groq, ONNX Runtime, Triton Inference Server, and TensorRT to minimize latency and cost.
• Design and implement agentic AI systems utilizing frameworks such as LangChain, AutoGPT, and ReAct for autonomous task orchestration.
• Fine-tune, integrate, and deploy foundation models including GPT, LLaMA, Claude, Mistral, Falcon, and others into intelligent applications.
• Develop and maintain robust MLOps workflows to manage the full model lifecycle including training, deployment, monitoring, and versioning.
• Collaborate with DevOps teams to implement scalable serving infrastructure leveraging containerization (Docker), orchestration (Kubernetes), and cloud platforms (AWS, GCP, Azure).
• Implement retrieval-augmented generation (RAG) pipelines integrating vector databases like FAISS, Pinecone, or Weaviate.
• Build observability systems for LLMs to track prompt performance, latency, and user feedback.
• Work cross-functionally with research, product, and operations teams to deliver production-grade AI systems handling real-world traffic patterns.
• Stay updated on emerging AI trends, hardware acceleration techniques, and contribute to open-source or research initiatives where possible.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
• 6–7 years of experience in machine learning engineering, applied AI, or MLOps roles.
• Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
• Deep knowledge of NLP, transformer-based architectures, and generative AI models.
• Hands-on experience with scalable LLM inference optimization using tools like vLLM, Groq, Triton Inference Server, TensorRT, or ONNX Runtime.
• Proven ability to serve AI models to concurrent users with low latency and high throughput.
• Experience in deploying ML systems on cloud platforms (AWS, GCP, Azure).
• Expertise in containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
• Familiarity with vector search technologies (FAISS, Pinecone, Weaviate) and RAG implementations.

Benefits

• Remote/PAN India options