Dreycey Albin

ML Software Engineer
at Microsoft Azure

resume.pdf

About Me

ML engineer focused on bridging research and production systems. I design deep learning architectures, build rigorous experimentation and evaluation frameworks, and ship low-latency decisioning infrastructure under strict reliability constraints. At Microsoft Azure, I serve as technical lead for modeling in the core control-plane ML system, Resource Central, serving all regions and processing over 1M requests daily.

Redmond, WA

education

Ph.D. Computer Science

University of Colorado Boulder · NSF GRFP Fellow

2020 – 2023

M.Sc. Systems, Synthetic & Physical Biology

Rice University

2018 – 2020

NIH-PREP Postbaccalaureate

University of Washington

2017 – 2018

B.S. Chemistry + B.S. Biology

University of Northern Colorado · McNair Scholar

2012 – 2017

stack

PyTorchTensorFlowScikit-LearnCUDADistributed TrainingRAGComputer VisionNLP

Service FabricKubernetesDockerAzure/AWSLinux/Git

PythonC++C#RustSQL (Postgres)NoSQL (Kusto/MongoDB)

Featured Publications

View All

PhageScanner: a reconfigurable machine learning framework for bacteriophage genomic and metagenomic feature annotation

Dreycey Albin, Michelle Ramsahoye, Eitan Kochavi, Mirela Alistar

Frontiers in Microbiology 2024 journal

paper code

PhageBox: an open source digital microfluidic extension with applications for phage discovery

Dreycey Albin, Lukas Buecherl, Eitan Kochavi, Elise Niehaus, Sasha Novack, Shenali Uragoda, Chris J. Myers, Mirela Alistar

IEEE TBME 2023 journal

paper code

SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning

Advait Balaji, Bryce Kille, Anthony D. Kappell, Gene D. Godbold, Madeline Diep, R. A. Leo Elworth, Zhiqin Qian, Dreycey Albin, Daniel J. Nasko, Nidhi Shah, Mihai Pop, Santiago Segarra, Krista L. Ternus, Todd J. Treangen

Genome Biology 2022 journal

paper code

Work Experience

ML Software Engineer

07/2023 – Present

Microsoft Azure · Redmond, WA

Unlocked $100M+/year in Azure CapEx and earned org-wide recognition by architecting and productizing an ML-driven CPU oversubscription capability.
Delivered ~$50M+/year in verified CapEx savings by leading technical execution of platform-wide policy changes validated through CapEx reporting.
Shipped ML inference that drives production control-plane behavior across Service Fabric microservices and legacy C# services.
Improved next-generation model quality (+6 pp offline accuracy) and production readiness by developing predictive models on large-scale time-series telemetry.
Delivered an internal RAG chatbot used for onboarding and knowledge discovery by designing the pipeline (LangChain + Semantic Kernel).

ML Software Engineer (Contract)

09/2021 – 05/2022

Medtronic · Boulder, CO

Led a small team to ship a production software stack for an autonomous catheter robot (Python backend, GUI, real-time motor control/integration).
Developed an LSTM catheter pose estimator that uses fiber-optic sensor data for real-time inference (sub 20ms/scan).