2–5 yrsBengaluruOn-siteDirect career pageEst. 12–24 LPA
Posted 20h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable backend services and APIs to support AI/ML applications in production.
- Productionize and optimize ML and deep learning models ensuring efficiency, reliability, and low-latency inference using frameworks like TensorRT, ONNX Runtime, Triton Inference Server, or FastAPI.
- Implement MLOps practices including model versioning, monitoring, automated deployments, and collaborate with cross-functional teams to deliver production-ready AI systems.
Minimum Requirements
- 2-5 years of work experience in AI Engineering.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or related fields.
- Strong proficiency in Python and backend frameworks like FastAPI; experience with AI model deployment frameworks (Triton, TensorRT, TorchServe, ONNX Runtime).
- Experience with cloud platforms (Azure, GCP), containerization (Docker), microservices architecture, CI/CD pipelines, and monitoring tools.
Ideal Candidate Profile
- Experienced in production-level AI/ML model serving and inference optimization in applied AI or enterprise environments.
- Skilled in integrating large language models (LLMs) and generative AI models into backend systems with prompt engineering expertise.
- Proficient in designing fault-tolerant, secure, and high-performance AI backend services with familiarity in MLOps and scalable data storage solutions.