Responsibilities & Key Deliverables
• Design, develop, and maintain backend services and APIs to support AI/ML applications at scale.
• Productionize ML and deep learning models, ensuring efficiency, reliability, and low-latency inference.
• Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments.
• Optimize AI model serving using frameworks such as TensorRT, ONNX Runtime, Triton Inference Server, or FastAPI.
• Implement MLOps practices including model versioning, monitoring, and automated deployments.
• Collaborate with AI researchers, data scientists, and product managers to translate prototypes into production-ready systems.
• Ensure robustness, fault tolerance, and security in backend AI systems.
• Integrate AI services with enterprise data platforms, cloud systems, and third-party APIs.
• Contribute to architecture discussions, design reviews, and performance tuning. Experience 2-5 Years of work experience in AI Engineering Industry Preferred Experience in working with Applied AI companies Qualifications
• Bachelor’s degree / Master’s degree with experience in Computer Science, Software Engineering, Data Science, or related fields.




• Preferred to have degree from a Tier-1/2 institute or a globally top-ranked university (as per QS). General Requirements Technical Requirements
• Strong proficiency in Python and backend frameworks (FastAPI).
• Expertise in Prompt engineering and working with various LLMs.
• Experience in productionizing AI/ML models with efficient inference pipelines.
• Hands-on experience with model deployment frameworks (Triton, TensorRT, TorchServe, ONNX Runtime).
• Knowledge of cloud platforms (Azure, GCP) and container technologies (Docker).
• Strong experience with microservices architecture, CI/CD pipelines, and monitoring tools (Prometheus, Grafana).
• Familiarity with databases (SQL/NoSQL) and scalable data storage solutions.
• Exposure to LLMs, SLMs, and GenAI model integration into backend systems is a solid plus.
• Understanding of security, authentication, and performance optimization in large-scale systems.
• Experience with version control (Git) and Agile development practices Our commitment to Diversity, Equity, and Inclusion

📌 AI Engineer (Bengaluru)
🏢 Mahindra and Mahindra
📍 Bengaluru