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I'm Aiden Sullivan, a Senior AI/ML Engineer with 8+ years of experience designing and deploying large-scale ML and LLM-powered systems in production. I specialize in RAG pipelines, transformer-based NLP, and real-time conversational AI architectures. I love building cloud-native, low-latency solutions and ML Ops pipelines across AWS, Azure, and GCP. I enjoy turning complex ideas into reliable, scalable platforms and mentoring teams to ship robust AI products.…I'm Aiden Sullivan, a Senior AI/ML Engineer with 8+ years of experience designing and deploying large-scale ML and LLM-powered systems in production. I specialize in RAG pipelines, transformer-based NLP, and real-time conversational AI architectures. I love building cloud-native, low-latency solutions and ML Ops pipelines across AWS, Azure, and GCP. I enjoy turning complex ideas into reliable, scalable platforms and mentoring teams to ship robust AI products.

Aiden Sullivan

AI Engineer, AI Developer, Full Stack Developer, +1

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I'm Aiden Sullivan, a Senior AI/ML Engineer with 8+ years of experience designing and deploying large-scale ML and LLM-powered systems in production. I specialize in RAG pipelines, transformer-based NLP, and real-time conversational AI architectures. I love building cloud-native, low-latency solutions and ML Ops pipelines across AWS, Azure, and GCP. I enjoy turning complex ideas into reliable, scalable platforms and mentoring teams to ship robust AI products.…I'm Aiden Sullivan, a Senior AI/ML Engineer with 8+ years of experience designing and deploying large-scale ML and LLM-powered systems in production. I specialize in RAG pipelines, transformer-based NLP, and real-time conversational AI architectures. I love building cloud-native, low-latency solutions and ML Ops pipelines across AWS, Azure, and GCP. I enjoy turning complex ideas into reliable, scalable platforms and mentoring teams to ship robust AI products.

Available to hire

I’m Aiden Sullivan, a Senior AI/ML Engineer with 8+ years of experience designing and deploying large-scale ML and LLM-powered systems in production. I specialize in RAG pipelines, transformer-based NLP, and real-time conversational AI architectures.

I love building cloud-native, low-latency solutions and ML Ops pipelines across AWS, Azure, and GCP. I enjoy turning complex ideas into reliable, scalable platforms and mentoring teams to ship robust AI products.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior AI/ML Engineer at Scale AI Systems

February 1, 2023 - Present

Designed and deployed real-time voice AI systems integrating Twilio, Deepgram, and ElevenLabs for automated conversational workflows. Architected low-latency WebSocket-based streaming for real-time AI inference. Built scalable FastAPI microservices and cloud-native infrastructure. Deployed AI systems across AWS, Azure, and GCP with HIPAA-aware workflows for healthcare automation. Developed ML models for prediction, classification, and data inference, plus end-to-end ML lifecycle and monitoring.

Machine Learning Engineer at Anki, Inc.

February 1, 2020 - January 1, 2023

Built production-ready ML APIs and backend services; designed ETL pipelines and distributed data workflows using Spark and Kafka. Implemented model monitoring and performance tracking; optimized system performance with caching and DB tuning. Contributed to early-stage data pipelines and automation workflows for model training and evaluation.

Machine Learning Engineer at Anki, Inc.

January 1, 2018 - January 1, 2020

Built feature extraction pipelines for structured and unstructured data; deployed ML models into production environments. Worked on early-stage distributed ML systems and data pipelines.

Machine Learning Developer at Anki, Inc.

March 1, 2016 - December 1, 2017

Assisted in development and training of machine learning models for classification and predictive analytics use cases. Built data preprocessing and feature engineering pipelines for structured and unstructured data. Supported deployment, testing, and validation of ML models in staging and production environments. Contributed to early-stage data pipelines and automation workflows for model training and evaluation.