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Jaan Hiienurm

@jaanhiienurm

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Senior AI/ML engineer building scalable LLM and RAG systems with measurable business impact.

Estonia

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What I'm looking for

I’m looking for a team where I can own end-to-end production AI—LLM/RAG systems, agentic workflows, and reliable MLOps—delivering measurable business impact through performance, observability, and secure enterprise integration.

I’m a Senior AI/ML Engineer with 10+ years of experience building, deploying, and operating production-grade AI systems at scale. I own the full model lifecycle—LLM integration, RAG pipelines, multimodal retrieval, and cloud-native infrastructure—so teams can ship reliable AI that performs under real-world constraints.

I’ve led end-to-end AI deployments serving millions of users, improving retrieval accuracy, reducing latency, and enabling enterprise-wide adoption. In recent roles, I architected RAG-based assistants, implemented agentic workflows with secure enterprise integrations, and set up observability for model drift, output consistency, and response latency—while cutting deployment time and infrastructure costs through automation, benchmarking, and efficient inference.

Experience

Work history, roles, and key accomplishments

Senior AI/ML Engineer

Method Grid

Feb 2022 - Feb 2026 (4 years)

Architected and deployed RAG-based AI assistants grounded on enterprise knowledge sources, improving answer relevance by 38% and reducing hallucinations by 27%. Built production LLM pipelines with monitoring and CI/CD automation, reducing model deployment time by 45%, and established observability for drift and response latency.

CI CD

AI/ML Engineer

ML6 (Skyrocket)

May 2020 - Jan 2022 (1 year 8 months)

Designed and deployed NLP pipelines, improving classification precision by up to 22%. Built and deployed RAG systems using open-source and OpenAI LLMs, fine-tuned and optimized GPU inference to reduce response latency by 35%, and delivered FastAPI-based inference services.

Docker fastAPI REST APIs

Machine Learning Engineer

Cgi Estonia

Jan 2016 - Apr 2020 (4 years 3 months)

Productionized multimodal retrieval across image, video, and text, improving ranking metrics (nDCG) by 18%. Built scalable embedding and vector search systems, benchmarked components to reduce query latency by 25%, and integrated AI features into user-facing applications.

Semantic Search Embeddings Vector Search Benchmarking Embedding Pipelines Ranking Optimization (NDCG)

Data Scientist

Helmes AS

Mar 2014 - May 2016 (2 years 2 months)

Built and deployed predictive models in production, improving business KPI performance by 20%+. Developed reproducible ML pipelines with CI/CD and automated testing, managed GCP resources for training and deployment, and implemented health-data compliance validation frameworks.

predictive modeling Automated Testing Google Cloud Platform (GCP)Data Validation Data Compliance