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Aiden SullivanAS
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Aiden Sullivan

@aidensullivan

Senior AI/ML engineer specializing in production LLM RAG, conversational AI, and low-latency distributed systems.

United States
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What I'm looking for

I’m looking to build production LLM/RAG and real-time conversational AI with strong MLOps ownership—deploying, monitoring, and improving models in low-latency distributed systems across cloud platforms.

I’m a Senior AI/ML Engineer with 8+ years of experience building large-scale machine learning and LLM-based systems for production. I specialize in RAG pipelines, transformer-based NLP, and real-time conversational AI architectures—turning models into reliable, low-latency experiences.

In my recent roles, I designed and deployed real-time voice AI systems with Twilio, Deepgram (STT), and ElevenLabs (TTS), and built WebSocket-based streaming infrastructure using FastAPI microservices. I also drive MLOps end-to-end—model deployment, monitoring, and lifecycle automation—across AWS, Azure, and GCP, including HIPAA-aware workflows for healthcare automation.

Experience

Work history, roles, and key accomplishments

Scale AI logoSA
Current

Senior AI/ML Engineer

Feb 2023 - Present (3 years 4 months)

Designed and deployed LLM-powered RAG systems for enterprise knowledge automation and conversational AI applications. Built low-latency WebSocket streaming and FastAPI microservices for real-time voice workflows, and implemented MLOps for model deployment, monitoring, and lifecycle automation across AWS, Azure, and GCP.

Covariant logoCO

AI/ML Engineer

Covariant

Feb 2020 - Jan 2023 (2 years 11 months)

Built machine learning models for prediction, classification, and data intelligence systems, and delivered production-ready ML APIs and backend services. Implemented ETL and distributed data workflows with Spark and Kafka, along with model monitoring and performance optimization through caching and database tuning.

JA

Machine Learning Engineer

Jawbone

Jan 2018 - Jan 2020 (2 years)

Developed NLP-based systems including classification, NER, and sentiment analysis, and built feature engineering pipelines for structured and unstructured data. Deployed machine learning models into production and contributed to early-stage distributed ML systems and data pipelines.

Education

Degrees, certifications, and relevant coursework

PU

Preston University

Bachelor of Science, Computer Science

Earned a Bachelor of Science in Computer Science from Preston University.

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