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PROBLEM SOLVING
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PROBLEM SOLVING

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aidyai/README.md

IDARA SAMUEL OSU — Machine Learning Engineer
Speech AI  •  Low-Latency Inference  •  Agentic Systems  •  Production MLOps


CORE STACK & TOOLING

Inference Engineering:
TensorRT-LLM vLLM SGLang CTranslate2 KV Caching Quantization In-Flight Batching

ML, NLP & Speech:
PyTorch Hugging Face LLMs Instruction Tuning NMT (Meta NLLB) TTS / STT Whisper Pipecat WebRTC / VAD

Agentic Frameworks:
LangGraph LangChain Multi-Agent Orchestration Tool / Function Calling

Cloud & MLOps Infrastructure:
AWS SageMaker Model Registry Multi-Model Endpoints Model Monitor Modal Docker CI/CD Supabase Python


TECHNICAL FOCUS & CAPABILITIES

Low-Latency Serving Stack
Compiling open-weight LLMs, Whisper, NMT, and TTS/STT models via TensorRT-LLM and CTranslate2; implementing KV caching, quantization, and in-flight batching for sub-second execution.
Full-Duplex Interactive Voice
Architecting real-time speech-to-speech pipelines using Pipecat with WebRTC, VAD-driven turn-taking, and barge-in support for conversational voice agents.
Agentic Orchestration
Designing stateful multi-tool routing environments and multi-agent coordination architectures using LangChain and LangGraph with function calling.
Cloud-Native MLOps & Production Pipelines
Building automated SageMaker Pipelines (preprocess, train, evaluate, register), multi-model endpoints, serverless inference layers, and automated CI/CD deployments with Docker.
Data Curation & Multilingual AI
Architecting raw dataset collection pipelines across multi-thousand-hour speech and text corpora for low-resource and zero-digital-footprint languages.

📬 Contact: idaraosusamuel@gmail.com | LinkedIn

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