Artificial Intelligence Engineer

Mahindra And Mahindra Limited; Bengaluru; In loco; INR 1.500.000 - 2.100.000; Tempo pieno

Descrizione del lavoro

Mahindra And Mahindra Limited is seeking an AI Engineer to design, build, and maintain backend services and APIs for AI/ML applications. You will productionize models for low-latency inference and deploy scalable microservices in enterprise environments.

You will optimize model serving with TensorRT, ONNX Runtime, Triton, or FastAPI, implement MLOps with versioning and monitoring, and work with researchers, data scientists, and PMs to turn prototypes into production-ready systems.

Competenze

• Bachelor’s or Master’s in Computer Science, Software Engineering, Data Science, or related fields.
• Degree from Tier-1/2 institute or top-ranked university (QS).
• 2–5 years of AI engineering experience.

Mansioni

• Design, develop, and maintain backend services and APIs for AI/ML apps at scale.
• Productionize ML/deep learning models with efficient inference.
• Build scalable microservices and REST/gRPC APIs for enterprise deployment.
• Optimize model serving using TensorRT, ONNX Runtime, Triton, or FastAPI.
• Implement MLOps: versioning, monitoring, and automated deployments.
• Collaborate with researchers, data scientists, and product managers to productionize prototypes.

Conoscenze

Python

FastAPI

Prompt engineering

LLMs

AI model deployment

CI/CD

Monitoring

Formazione

Bachelor’s or Master’s in CS/Software/Data Science

Strumenti

Docker

TensorRT

TorchServe

ONNX Runtime

Triton Inference Server

Prometheus

Grafana

Descrizione del lavoro

AI Engineer 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

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 strong 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

Experience Level

Mid Level