Mark Hoffmann
Staff Machine Learning Engineer at Meta
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolMark Hoffmann is a Staff Machine Learning Engineer based in Palo Alto with 11 years of experience building production ML systems across startups, government labs, and hyperscale platforms. He has driven ads ranking and ML foundation work at Meta while previously serving as Chief Architect at a signal-intelligence startup where he built real-time ML platforms ingesting high-velocity RF data and led a 14-engineer org. At NASA JPL he applied AutoML, neural architecture search, reinforcement learning, and anomaly detection to space operations and mission-critical telemetry, bringing rigorous uncertainty quantification to hardware and scheduling problems. His background blends hands-on research (DARPA AutoML and active-learning programs) with practical system design: model-system co-design, compression, distillation, and cost-optimized cloud architectures. He holds a Masters of Analytics and an engineering-physics undergraduate grounding that explains his comfort at the intersection of physical systems and learning algorithms. Colleagues see him as a pragmatic innovator who moves cutting-edge research into resilient, scalable production.
11 years of coding experience
13 years of employment as a software developer
Masters of Analytics, Masters of Analytics at North Carolina State UniversityMajor: Engineering Physics Minors: Computer Science & Math, Major: Engineering Physics Minors: Computer Science & Math at Augustana College
Github Skills (50)
bottle9
django9
xception9
aws-lambda9
icd9
lambda9
pyramid9
uid9
credit9
flask9
resnet9
serverless8
python8
serverless-framework8
api-gateway8
Programming languages (7)
Github contributions (5)
mark-hoffmann/icd
Oct 2017 - Apr 2021
Tools for working with icd codes and comorbidities
Contributions:4 commits, 2 PRs, 13 pushes in 3 years 7 months
crediticduid
mark-hoffmann/fastteradata
Oct 2017 - Jul 2018
Tools for faster and optimized interaction with Teradata and large datasets.
Contributions:9 PRs, 65 pushes, 7 branches in 8 months
teradata
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