Jack Doyle
@jackdoyle
Senior ML engineer specializing in LLM systems, RAG pipelines, and production-grade AI automation.
What I'm looking for
I am a Senior ML Engineer and LLM specialist with extensive hands-on experience designing and deploying Multi-Agent Systems, RAG-based pipelines, and LLM-driven automation across healthcare and enterprise domains. I bridge research and engineering by fine-tuning open-source LLMs (QLoRA, DPO), building agent orchestration frameworks with LangChain/LangGraph/LangSmith, and delivering production-ready, scalable AI products.
My career highlights include leading end-to-end healthcare AI projects, building scalable AI research platforms with dual-LLM integrations and FastAPI–WebSocket architectures, and deploying customer-facing solutions such as chatbots backed by Neo4j graph knowledge bases. I prioritize observability, evaluation (Ragas, A/B testing), and robust MLOps to ensure reliable, high-impact outcomes for stakeholders.
Experience
Work history, roles, and key accomplishments
Led end-to-end development of healthcare AI systems, building multi-agent LLM workflows and RAG pipelines that improved research automation and production reliability; fine-tuned open-source LLMs and delivered customer-facing chatbots with graph-structured reasoning.
Data & AI Engineer
Mercari
Jul 2021 - May 2023 (1 year 10 months)
Implemented MLOps pipelines and production model deployments on EKS, developed recommendation systems that increased engagement 9% and sales 12%, and built PySpark ETL pipelines to produce high-value features for ML models.
AI & Web3 Engineer
Token Metrics
Apr 2019 - Jul 2021 (2 years 3 months)
Built automated ETL pipelines ingesting DeFi on-chain data and deployed forecasting models on SageMaker with canary strategies; developed real-time crypto market intelligence dashboards and resilient microservices on Kubernetes.
Developed features for a high-performance e‑commerce SaaS, led migration from monolith to microservices using Kafka, and implemented CI/CD and IaC to streamline deployments and ensure compliance with global payment standards.
Education
Degrees, certifications, and relevant coursework
Technological University Dublin
Master of Science, Applied Data Science
2015 - 2017
Master of Science in Applied Data Science focusing on advanced data analysis, machine learning, and applied AI techniques.
Technological University Dublin
Bachelor of Science, Computer Science
2011 - 2015
Bachelor of Science in Computer Science covering software engineering, algorithms, and data systems.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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