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I'm a Senior AI/ML Engineer with an M.Sc. in Statistics, specializing in building and deploying mathematically rigorous, high-scale production systems. With 5+ years of experience, I bridge the gap between advanced research and reliable software delivery. I provide deep expertise in these critical areas: Production AI/LLM Engineering: Technical leadership in designing and deploying scalable AI platforms, including RAG pipelines, multi-model integration, and high-availability deployment using Kubernetes and Docker. High-Performance ML Systems: Managing the full ML service lifecycle, scaling to millions of inferences/year. Expertise includes developing low-latency back-end services in Rust and optimizing model compilation using PyTorch/Onnx. Advanced Statistical Optimization: Developing and deploying complex statistical models (Bayesian methods, changepoint analysis, risk forecasting) and sophisticated mathematical optimization algorithms (Integer, Convex, Nonlinear Programming) for critical business needs.…I'm a Senior AI/ML Engineer with an M.Sc. in Statistics, specializing in building and deploying mathematically rigorous, high-scale production systems. With 5+ years of experience, I bridge the gap between advanced research and reliable software delivery. I provide deep expertise in these critical areas: Production AI/LLM Engineering: Technical leadership in designing and deploying scalable AI platforms, including RAG pipelines, multi-model integration, and high-availability deployment using Kubernetes and Docker. High-Performance ML Systems: Managing the full ML service lifecycle, scaling to millions of inferences/year. Expertise includes developing low-latency back-end services in Rust and optimizing model compilation using PyTorch/Onnx. Advanced Statistical Optimization: Developing and deploying complex statistical models (Bayesian methods, changepoint analysis, risk forecasting) and sophisticated mathematical optimization algorithms (Integer, Convex, Nonlinear Programming) for critical business needs.

Andrew Muth

AI Engineer, Data Scientist, DevOps Developer, +5

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I'm a Senior AI/ML Engineer with an M.Sc. in Statistics, specializing in building and deploying mathematically rigorous, high-scale production systems. With 5+ years of experience, I bridge the gap between advanced research and reliable software delivery. I provide deep expertise in these critical areas: Production AI/LLM Engineering: Technical leadership in designing and deploying scalable AI platforms, including RAG pipelines, multi-model integration, and high-availability deployment using Kubernetes and Docker. High-Performance ML Systems: Managing the full ML service lifecycle, scaling to millions of inferences/year. Expertise includes developing low-latency back-end services in Rust and optimizing model compilation using PyTorch/Onnx. Advanced Statistical Optimization: Developing and deploying complex statistical models (Bayesian methods, changepoint analysis, risk forecasting) and sophisticated mathematical optimization algorithms (Integer, Convex, Nonlinear Programming) for critical business needs.…I'm a Senior AI/ML Engineer with an M.Sc. in Statistics, specializing in building and deploying mathematically rigorous, high-scale production systems. With 5+ years of experience, I bridge the gap between advanced research and reliable software delivery. I provide deep expertise in these critical areas: Production AI/LLM Engineering: Technical leadership in designing and deploying scalable AI platforms, including RAG pipelines, multi-model integration, and high-availability deployment using Kubernetes and Docker. High-Performance ML Systems: Managing the full ML service lifecycle, scaling to millions of inferences/year. Expertise includes developing low-latency back-end services in Rust and optimizing model compilation using PyTorch/Onnx. Advanced Statistical Optimization: Developing and deploying complex statistical models (Bayesian methods, changepoint analysis, risk forecasting) and sophisticated mathematical optimization algorithms (Integer, Convex, Nonlinear Programming) for critical business needs.

Available to hire

I’m a Senior AI/ML Engineer with an M.Sc. in Statistics, specializing in building and deploying mathematically rigorous, high-scale production systems. With 5+ years of experience, I bridge the gap between advanced research and reliable software delivery.

I provide deep expertise in these critical areas:

Production AI/LLM Engineering: Technical leadership in designing and deploying scalable AI platforms, including RAG pipelines, multi-model integration, and high-availability deployment using Kubernetes and Docker.

High-Performance ML Systems: Managing the full ML service lifecycle, scaling to millions of inferences/year. Expertise includes developing low-latency back-end services in Rust and optimizing model compilation using PyTorch/Onnx.

Advanced Statistical Optimization: Developing and deploying complex statistical models (Bayesian methods, changepoint analysis, risk forecasting) and sophisticated mathematical optimization algorithms (Integer, Convex, Nonlinear Programming) for critical business needs.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI Engineer II, Platform Engineering at Kraken

April 1, 2025 - November 17, 2025

Led and served as Technical Lead for automating compliance due diligence for new token listings using LLMs to generate legal and regulatory documentation. Built and maintained the centralized LLM Platform with scalable RAG data pipelines and multi-model integration, deployed via Kubernetes, Helm, and Docker. Contributed to a high-availability, customer-facing chatbot's back-end services in Rust for low latency and reliability.

Data Scientist II, Compliance/Engineering at Kraken

April 1, 2025 - April 1, 2025

Collaborated across Operations and Engineering to design and deploy real-time ML services, scaling to millions of inferences/year. Managed the lifecycle of AWS-based configuration ML services, enabling daily rescoring of over 2M clients across multiple regulatory jurisdictions for AML risk. Contributed to production-ready ONNX/PyTorch tooling to compile business logic/models into efficient byte code.

Sr. Data Scientist/Statistician, Technical Lead at Neo Financial

October 1, 2022 - October 1, 2022

Led Bayesian regression analyses using STAN to measure the Neo Rewards program impact, and developed probabilistic credit risk forecasting models to identify delinquent cardholders for proactive interventions, reducing defaults. Trained real-time fraud-detection models, decreasing fraud losses by 80–90%. Built a graph database on Apache Spark to map fraudulent activity and support compliance workflows.

Data Scientist/Statistician at Neo Financial

November 1, 2021 - November 1, 2021

Designed experiments (A/B, factorial, synthetic control) to assess rewards program effectiveness and led development of high-performance heuristic optimization for the rewards network. Identified key customer segments via regression mixtures and detected behavioral shifts with changepoint methodologies to inform targeted marketing.

AI Engineer II at Kraken

April 1, 2025 - November 17, 2025

Spearheaded and served as Technical Lead for automating compliance due diligence for new token listings, leveraging LLMs to generate legal and regulatory documentation. Engineered and maintained the centralized LLM Platform, building and optimizing RAG data pipelines, enabling multi-model integration and high-scale deployment via Kubernetes, Helm, and Docker. Core contributor for the high-availability, customer-facing chatbot with Rust-based backend services to ensure low-latency performance and production reliability.

Data Scientist II at Kraken

April 1, 2025 - April 1, 2025

Collaborated across Ops and Engineering to design real-time ML services scalable to millions of inferences/year; managed lifecycle of configuration-based ML services on AWS, facilitating daily rescoring of over 2M clients across multiple regulatory jurisdictions for AML risk; contributed to an Onnx & PyTorch based library for production bytecode compilation.