Company Overview

Sarvam.ai is a pioneering generative AI startup headquartered in Bengaluru, India. Our mission is to make generative AI accessible and impactful for Bharat. Founded by a team of AI experts, Sarvam.ai is dedicated to developing cost-effective, high-performance AI agents tailored for the Indian market, enabling enterprises to tap into new opportunities and foster deeper customer connections. Join us in reshaping AI for India and beyond.

Job Summary

We are looking for a skilled Backend Engineer proficient in Python with a strong foundation in AI/ML to join our growing team. As a Backend Engineer, your primary focus will be designing and developing high-performance, low-latency backend systems that serve AI-driven applications, including LLMs, retrieval-augmented generation (RAG), and deep learning models. You will work on model training, fine-tuning, quantization (QLoRA), reinforcement learning (DPO), and efficient deployment of LLMs, ensuring reliability, scalability, and cost efficiency.

Key Responsibilities

• Backend Development: Design, develop, and maintain scalable and efficient backend applications and RESTful services using Python and FastAPI.

• AI & Model Engineering: Work on training, fine-tuning, and optimizing LLMs for non-standard tasks, including low-latency inference, quantization (QLoRA), and LoRA fine-tuning.

• Retrieval-Augmented Generation (RAG): Develop and optimize AI-driven retrieval systems, integrating knowledge bases with LLMs to enhance response accuracy.

• Model Deployment & Performance Optimization: Deploy and manage AI models in production environments, focusing on scalability, efficiency, and cost reduction.

• Data Pipelines & Orchestration: Develop and manage data pipelines to facilitate efficient training and inference workflows.

• Reliability & Scalability: Ensure backend services and AI models run with high availability, fault tolerance, and minimal latency.

• DevOps & MLOps Integration: Implement CI/CD pipelines, containerized deployments (Docker, Kubernetes), and version-controlled model training workflows.

• Collaboration: Work closely with AI researchers, data scientists, and ML engineers to integrate cutting-edge AI advancements into production systems.

Must-Have Skills and Qualifications

• Educational Background: Bachelor's degree in Computer Science, Engineering, or related field (2024/2025 graduates).

• Programming Foundation: Strong understanding of programming concepts with proficiency in Python.

• Web Technologies: Experience in building RESTful APIs and working with FastAPI, Flask, or Django.

• Database Knowledge: Familiarity with SQL and NoSQL databases for structured and unstructured data management.

• Deep Learning & LLMs:

  • Hands-on experience with deep learning frameworks (TensorFlow, PyTorch).

  • Experience in training, fine-tuning, and deploying LLMs for AI applications.

  • Understanding of LoRA, QLoRA, and other fine-tuning techniques.

  • Experience working on low-latency, quantized AI models.

  • Experience with Direct Preference Optimization (DPO) for model alignment.

• Experience with RAG Systems: Prior exposure to retrieval-augmented generation (RAG) architectures and building AI-driven retrieval systems.

• Version Control: Strong understanding of Git and best practices in version control.

• Problem Solving: Strong analytical and debugging skills.

• Soft Skills: Excellent communication, teamwork, and problem-solving abilities.

Good to Have

• Backend Projects: Academic or personal projects involving backend development and AI model integration.

• Cloud Exposure: Basic understanding of cloud platforms (AWS, GCP, Azure).

• Development Tools: Familiarity with Linux/Unix environments, containerization (Docker, Kubernetes), and serverless architectures.

• CI/CD & MLOps: Experience setting up CI/CD pipelines for automated model training, testing, and deployment.

Open Source Contributions: Strong GitHub portfolio or contributions to open-source AI/ML projects.