Jacob Marks
Technical Staff, Superintelligence at Meta
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJacob Marks is a technical staff researcher focused on post-training safety and capabilities work at Meta's Superintelligence Lab, with nine years of experience spanning deep learning, data-centric AI, and theoretical physics. He holds a PhD in theoretical physics from Stanford and has translated that rigorous background into applied ML roles at Liquid AI and Voxel51, where he contributed notable computer vision tooling and integrations for the popular FiftyOne project. As an entrepreneur he founded and scaled a startup from idea to revenue, and his resume includes moonshot research at X (Google X) developing classical and quantum energy-based models. Jacob combines production ML engineering, research fluency, and developer evangelism—comfortable shipping evaluation tooling, model visualizations, and dataset-centric workflows. Based in San Francisco, he bridges high-risk research and pragmatic engineering, often surfacing practical improvements born from deep theoretical insight.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS Intensive Physics Math and Philosophy each with Distinction, Bachelor of Science - BS Intensive Physics Math and Philosophy each with Distinction at Yale UniversityHigh School, High School at Hopkins schoolDoctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at Stanford University
English, Chinese, c/c++, python, matlab, latex, mathematica
Stackoverflow
21reputation
259reached
1answer
0questions
Github Skills (12)
yolov810
huggingface-transformers10
computer-vision10
machine-learning10
eval10
python10
evaluation10
object-detection9
image-classification8
documentation7
fiftyone6
datasets6
Programming languages (6)
Github contributions (5)
voxel51/fiftyone
Oct 2022 - Jan 2023
Refine high-quality datasets and visual AI models
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:101 reviews, 8 commits, 116 PRs in 2 months
Contributions summary:Jacob contributed to the development and documentation of computer vision models, specifically around the integration and evaluation of YOLOv8 and other deep learning models within the FiftyOne ecosystem. The user implemented tools for loading and applying models from the Ultralytics and Hugging Face Hubs, converting model predictions to FiftyOne formats, and evaluating model performance. Additionally, the user worked on implementing enhancements to the visualization and analysis capabilities within the FiftyOne app.
aimachine-learningartificial-intelligencedeep-learningcomputer-vision
jacobmarks/zero-shot-prediction-plugin
Sep 2023 - Jan 2025
Run zero-shot prediction models on your data
Contributions:5 reviews, 4 PRs, 25 pushes in 1 year 3 months
prediction-modelclassificationclipcomputer-visiondetection
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