Dan S
Lead Software Engineer at dolaGon
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolDan S is a Lead Software Engineer in New York with 15 years of experience building high-performance, research-driven systems across robotics, autonomous vehicles, and scientific Python ecosystems. He blends backend systems and ML/Probabilistic programming expertise—contributing to flagship open-source projects like PyMC, TensorFlow/XLA, JAX, and Astropy—bringing practical improvements to HMC mass-matrix adaptation, KDE in JAX, and exoplanet-detection tooling. At Caterpillar he architected middleware-agnostic frameworks and HIL simulation benches for autonomous systems, and he has a track record of shipping low-level C/C++ and embedded solutions as well as visualization and tooling for validation. Comfortable leading teams (Scrum, 18 engineers) and diving into math-heavy code, he pairs strong production engineering with academic curiosity, routinely reading research and presenting findings. Currently on parental leave, he remains active in open-source and builds cross-domain bridges between robotics, probabilistic modeling, and systems engineering.
15 years of coding experience
6 years of employment as a software developer
BS - Computer Science, Computer Science, BS - Computer Science, Computer Science at NYU Tandon School of EngineeringBrooklyn Technical High School
English, Russian
Github Skills (64)
algorithm10
data-visualizations10
algorithms10
c-language10
probabilistic-programming10
mc10
python10
optimizers10
redis10
astronomy10
matplotlib10
testing10
statistics10
machine-learning10
optimizer10
Programming languages (21)
Github contributions (5)
dfm/osrc
Apr 2013 - Dec 2016
The Open Source Report Card
Role in this project:
Back-end Developer
Back-end DeveloperContributions:199 commits, 8 PRs, 37 pushes in 3 years 9 months
Contributions summary:Dan contributed to the scraping script by adding the initial implementation and more information in the database. This involved creating the `fetch.py` script, which uses Python, along with the appropriate imports. They also included the addition of a visualization, with the inclusion of `www/index.html` and `www/js/d3.v3.min.js`, thus creating the initial steps for the frontend. Further commits also included the addition of a k-means script.
reportreport-card
dfm/emcee
Aug 2010 - Dec 2022
The Python ensemble sampling toolkit for affine-invariant MCMC
Role in this project:Back-end Developer
Back-end DeveloperContributions:19 releases, 3 reviews, 780 commits in 12 years 6 months
Contributions summary:Dan was primarily involved in developing functionality for the "emcee" package, a Python ensemble sampling toolkit for affine-invariant MCMC. Their work focused on expanding the package's capabilities through the addition of new features. They introduced a class for a parallel-tempered ensemble sampler, new moves for generating proposals, and a HDF5-based backend for storing the MCMC chains.
mcmc-samplerpythonprobabilistic-data-analysisensembleinvariant
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