Dreycey Albin

Dreycey Albin

ML Software Engineer
at Microsoft Azure

About Me

ML engineer with roots in computational biology and a focus on bridging research and production systems. I design and validate ML/deep learning models, build experimentation frameworks, and ship low-latency inference pipelines. At Microsoft Azure, I work at the intersection of modeling and distributed services on Resource Central, serving all regions at 1M+ requests per day.

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
B.S. Chemistry + B.S. Biology
University of Northern Colorado · McNair Scholar
2012 – 2017
interests
Computational BiologyGenerative AIML SystemsDistributed Systems

Work Experience

Microsoft Azure

Redmond, WA
Machine Learning Engineer, Level 62 03/2025 – Present

Drove high-impact ML and infrastructure work spanning capacity optimization, predictive modeling, and distributed systems. Designed a telemetry-driven capacity mitigation system that reduced regional response times from ~1 week to ~4 hours across 50+ regions and ~1M VMs — recognized with an org-wide Azure Impact Award. Leading a cross-functional team on a DNN for heterogeneous resource-consumption prediction integrated into the Azure control plane at ≤50ms SLO. Architected a distributed model delivery platform with automated versioning, shadow/canary releases, and rollback guardrails.

Machine Learning Engineer, Level 61 07/2023 – 03/2025

Drove platform-wide capacity policy changes with automated validation and CapEx reporting used by finance and senior leadership. Overhauled the production model evaluation framework with thresholding tradeoff analysis and backtesting across cohorts, improving model quality while preserving safety constraints.

Medtronic

Boulder, CO
Research Software Engineer, Contract 09/2021 – 05/2022

Developed a real-time LSTM pose estimator from fiber-optic sensor streams for surgical catheter tracking, and shipped the full production Python software stack for an autonomous catheter robot including real-time control, telemetry, and failure-safe behaviors that passed regulatory-readiness review.

Software / Projects

EnrichSeq

EnrichSeq

A bioinformatics pipeline for phage enrichment analysis.

Python / Nextflow / Bash
PhageBox

PhageBox

Embedded system for bacteriophage research automation.

C/C++
PhageScanner

PhageScanner

A reconfigurable machine learning pipeline for labeling ORFs/proteins in bacteriophage genomes and metagenomic data.

Python
PhageFilter

PhageFilter

PhageFilter uses a Sequence Bloom Tree (SBT) to filter bacteriophage reads from metagenomic files.

Rust
Metscale

Metscale

Metagenomics analysis workflow.

Snakemake / Python
SeqScreen

SeqScreen

Sequence screening pipeline.

Python / Bash / Nextflow
Kvar

Kvar

Bioinformatics tool.

Bash / Python / R

Contact

Feel free to reach out for collaborations or questions.