Daniel Martin-alarcon
MLOps Software Engineer at Dayhoff Labs
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolDaniel Martin-alarcon is an MLOps software engineer and synthetic biologist with 8 years of experience building production-ready ML pipelines for industrial and biotech applications. Based in San Francisco, he combines a PhD in Biological Engineering from MIT with hands-on expertise in Docker, DVC, Dagster, and distributed GCP compute to make research reproducible and scalable. At Dayhoff Labs he designed core infrastructure—from custom containerized environments to data versioning and orchestration—that allowed scientists to move from exploratory code to reliable, auditable workflows. Previously he led end-to-end data engineering and cloud deployments for IoT and biotech startups, championing test-driven development and infrastructure-as-code. He also brings experience in grant writing and science advising, a rare blend that helps translate technical needs into funded research programs.
8 years of coding experience
4 years of employment as a software developer
PhD Biological Engineering, PhD Biological Engineering at Massachusetts Institute of TechnologyExchange student Chemical Engineering, Exchange student Chemical Engineering at TU Dortmund UniversityBS Chemical Engineering, BS Chemical Engineering at New Mexico State University
German, Spanish, English
Github Skills (69)
qbcore-framework8
abaqus7
terminology7
opcodes7
water7
timing7
crossword7
canopen7
ansible-collections7
tricks7
lgbt7
loops6
lda6
sprint6
science6
Programming languages (4)
Github contributions (5)
DanielMartinAlarcon/Arsenic-and-Fluoride-Mexico
Jul 2019 - Apr 2021
Fully reproducible analysis of a water pollution dataset.
Contributions:14 commits, 7 PRs, 11 pushes in 1 year 9 months
pythondatasetmachine-learningreproduciblewater
labs12-should-i-live-here/DS
Apr 2019 - May 2019
Contributions:81 commits, 25 PRs, 53 pushes in 1 month
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