2 - 5 years

Bengaluru

Posted:15 hours ago

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Job Description

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 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


Job Segment: Software Engineer, Engineer, Engineering

Skills Required

Backend Ai/ml Deep Learning Microservices AI Solutions Third Party Performance Tuning Computer Science Software Engineering Data Science Python Cloud Platforms

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