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AI Platform Engineer

AI Platform Engineer

T-Pro

0 years

0 Lacs

greater kolkata area

Posted:1 day ago| Platform:

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Skills Required

ai cutting recognition developer inference server api development design documentation model deployment latency scalability reliability monitoring logging auto scaling collaboration research devops automate programming python fastapi flask node.js docker kubernetes rest websockets aws gcp azure distillation onnx

Work Mode

On-site

Job Type

Full Time

Job Description

We are seeking an

AI Platform Engineer

to build and scale the infrastructure that powers our production AI services. You will take cutting-edge models-ranging from

speech recognition (ASR)

large language models (LLMs),

and deploy them into highly available, developer-friendly APIs.You will be responsible for creating the bridge between the

R&D team

, who train models, and the

applications

that consume them. This means developing robust APIs, deploying and optimising models on

Triton Inference Server (or similar frameworks)

, and ensuring real-time, scalable inference.

Responsibilities

API Development

Design, build, and maintain production-ready APIs for speech, language, and other AI models.
Provide SDKs and documentation to enable easy developer adoption.

Model Deployment

Deploy models (ASR, LLM, and others) using Triton Inference Server or similar systems.
Optimise inference pipelines for low-latency, high-throughput workloads.

Scalability & Reliability

Architect infrastructure for handling large-scale, concurrent inference requests.
Implement monitoring, logging, and auto-scaling for deployed services.

Collaboration

Work with research teams to productionize new models.
Partner with application teams to deliver AI functionality seamlessly through APIs.

DevOps & Infrastructure

Automate CI/CD pipelines for models and APIs.
Manage GPU-based infrastructure in cloud or hybrid environments.

Requirements

Core Skills

Strong programming experience in Python (FastAPI, Flask) and/or Go/Node.js for API services.
Hands-on experience with model deployment using Triton Inference Server, TorchServe, or similar.
Familiarity with both ASR frameworks and LLM frameworks (Hugging Face Transformers, TensorRT-LLM, vLLM, etc.).

Infrastructure

Experience with Docker, Kubernetes, and managing GPU-accelerated workloads.
Deep knowledge of real-time inference systems (REST, gRPC, WebSockets, streaming).
Cloud experience (AWS, GCP, Azure).

Bonus

Experience with model optimisation (quantisation, distillation, TensorRT, ONNX).
Exposure to MLOps tools for deployment and monitoring

More Jobs at T-Pro

AI Platform Engineer

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