Open to opportunities

Ryan Smith

@ryansmith4

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Senior Machine Learning Engineer specializing in LLMs, MLOps, and scalable GenAI systems.

United States

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What I'm looking for

I seek roles building production GenAI/LLM systems with strong MLOps, low-latency inference, multi-cloud deployment, and collaborative engineering culture.

I am a Senior Machine Learning Engineer with over 10 years building production-grade AI/ML systems across NLP, computer vision, and time-series forecasting. I design and deploy LLM-driven solutions, RAG pipelines, and low-latency inference stacks using tools like Triton, ONNX, and multi-cloud GPU infrastructure.

My work spans fine-tuning and quantization (LoRA, QLoRA, 4-bit/8-bit), building MLOps ecosystems with CI/CD, monitoring, and auto-scaling, and integrating retrieval systems using LangChain, FAISS, and Pinecone. I have driven measurable improvements such as 40% reduction in hallucinations, sub-500ms inference latency, and 60% latency improvements under load.

I partner with engineering and data teams to deliver reliable GenAI applications—document Q&A, summarization agents, voice assistants, recommender systems—and emphasize model governance, observability, and cost-efficient, multi-cloud deployments to turn ML research into production impact.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

PivotKing LLC

May 2024 - Present (2 years 1 month)

Spearheaded design and deployment of LLM-driven conversational AI and RAG pipelines, reducing hallucinations by 40% and improving inference latency by 60% through quantization and optimized serving.

LLM RAG LoRA QLoRA Model Quantization Triton Onnx Faiss Pinecone

Senior AI Software Engineer

PivotKing LLC

May 2023 - Apr 2024 (11 months)

Designed and deployed transformer-based NLP pipelines achieving 94% macro F1 on 1M+ documents and automated CI/CD model delivery to enable zero-downtime updates and reduced latency.

Transformer Models NLP CI CD Docker Kubernetes MLFlow Prometheus Spark BigQuery

Machine Learning Engineer

Plainsight

Aug 2021 - Aug 2023 (2 years)

Built a document intelligence system processing 50K+ pages/day with 98% layout recall and 93% NER F1, and developed time-series forecasting that cut forecast error by 22%.

Computer Vision BERT Time Series Prophet Tsfresh Model Governance AIF360 TsFresh

Data Scientist

Wootric

Feb 2017 - Jul 2021 (4 years 5 months)

Built a demand forecasting engine processing 10TB+ weekly, achieving 90%+ accuracy across 200+ SKUs and reduced ETL processing costs by 40% via Spark optimizations.

XGBoost LightGBM Optuna Spark Parquet Anomaly Detection

Software Engineer Intern

Cisco

Oct 2016 - Feb 2017 (4 months)

Developed LDA topic modeling and collaborative filtering for support tickets, automating routing to 85% accuracy and improving first-contact resolution by 18%.

LDA Topic modeling Flask D3.Js Collaborative Filtering Python

Data Scientist

Aerohive Networks

May 2015 - Sep 2016 (1 year 4 months)

Built predictive analytics for network traffic with 92% accuracy, automated Spark-based ingestion reducing processing time by 40%, and deployed real-time anomaly detection lowering false positives by 28%.

XGBoost Random Forest Spark Anomaly Detection Isolation Forest