Overview
Join to apply for the AI Platform Engineer role at T-Pro.
We are seeking an AI Platform Engineer to build and scale the infrastructure that powers our production AI services. You will work with models ranging from speech recognition (ASR) to large language models (LLMs), and deploy them into highly available, developer-friendly APIs. You will bridge the gap between the R&D team who train models and the applications that consume them, 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 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.
Employment & Functions
* Employment type: Full-time
* Job function: Engineering and Information Technology
* Industries: IT System Custom Software Development
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