DevOps Engineer | SDE - 1 | SDE  - 2

Role: Senior ML/AI Engineer - Platform & LLM Systems

Function: Machine Learning Engineering

Location: Mumbai, India

Type: Full-time

Compensation: Not specified

Industry: AI/ML, Technology Infrastructure

About Company

The company is building the AI layer for Bharat at India-scale. Backed by partnerships with global tech leaders like Meta and Google, the team is creating AI that serves the entire Indian user base—across languages, contexts, and daily needs. This is AI designed for real adoption, not experiments.

They bring a rare combination of deep India-first AI capability and unmatched India-scale distribution. The focus is a platform-and-product stack that makes AI useful, reliable, and safe for everyday consumers. It’s engineered from day one for massive scale—100M+ users early and 1B-ready constraints on latency, cost, reliability, and safety.

If you want to be part of a fast-moving, high-ambition team building technology with real-world reach, this is that opportunity. The culture emphasises engineering excellence, strong collaboration, and tangible impact across sectors that matter to India—while building toward a category-defining consumer AI experience.

Position Overview

You'll lead the development of the company's AI backbone, building sophisticated agentic workflows and LLM inference systems that serve millions of users across India's diverse sectors. You'll architect vector graph retrieval systems and platform-level AI services that integrate with existing infrastructure ecosystem. This role offers direct impact on AI solutions spanning education, healthcare, and agriculture while working with global tech leaders on India's largest AI initiative.

Role & Responsibilities

• Design and implement large-scale LLM inference systems and agentic workflows for production environments
• Build and optimize vector graph retrieval systems for real-time AI applications
• Develop platform-level AI services that integrate with the company's existing infrastructure ecosystem
• Architect RAG pipelines and embedding systems for knowledge retrieval at scale
• Collaborate with cross-functional teams to deploy AI models serving millions of users
• Optimize ML model performance and inference latency for production workloads
• Contribute to open-source AI initiatives and maintain high engineering standards

Must Have Criteria

• 5-10 years of hands-on ML engineering or platform-oriented AI development experience
• Expert-level proficiency in Python and PyTorch for production ML systems
• Proven experience building RAG systems, embeddings, and working with LLMs in production
• Hands-on experience with vector databases (Pinecone, Weaviate, or Chroma) for similarity search
• Experience scaling AI systems serving 50M+ daily active users or equivalent scale
• Strong understanding of distributed systems and microservices architecture
• Track record of building platform-level AI services or ML infrastructure

Nice to Have

• Experience with Kubernetes orchestration and container-based ML deployments
• Cloud platform expertise in AWS or Azure for ML workloads
• Background in agentic AI systems or autonomous workflow development
• Open-source contributions to ML/AI frameworks or libraries
• Experience with multi-modal AI systems or computer vision applications

What We Offer

• Opportunity to build AI infrastructure at gigawatt scale with green energy backing
• Collaboration with global tech leaders and access to cutting-edge AI research
• Impact millions of users across education, healthcare, and agriculture sectors
• Fast-track career growth in India's largest AI initiative
• Comprehensive benefits and competitive compensation package