SpectralName
Joined 5 years ago
Joined 5 years ago
Location: NY State, US
Remote: Yes
Willing to relocate: No
Technologies: Python (BE - Django, FastAPI; data science - numpy/pandas; ML - pytorch/ONNX/torchscript/Triton), Kafka
Résumé/CV: https://drive.google.com/file/d/1xfpNaajacqC46E-P5PuQwn9KsG7lUmfa/view?usp=sharing
Email: [email protected]
MLE with 5 YoE - 4 in computer vision R&D, 2 with LLMs and SaaS. The arc of my career so far has been a slow evolution from Research Engineer towards AI-assisted full stack web dev. I'm interested in working in AI4Science, climate tech, or anywhere with a compelling story about how you're making the world a better place. I'm comfortable figuring out whatever needs doing and doing it in a small org, but I'm happiest when I get to implement a paper every so often, and when I get to help technical but non-programmer SMEs solve problems they didn't realize could be solved. Location: NY State, US
Remote: Yes
Willing to relocate: No
Technologies: Python (BE - Django, FastAPI; data science - numpy/pandas; ML - pytorch/ONNX/torchscript/Triton), Kafka
Résumé/CV: https://drive.google.com/file/d/1xfpNaajacqC46E-P5PuQwn9KsG7lUmfa/view?usp=sharing
Email: [email protected]
MLE with 5 YoE - 4 in computer vision R&D, 2 with LLMs and SaaS. The arc of my career so far has been a slow evolution from Research Engineer towards AI-assisted full stack web dev. I'm interested in working in AI4Science, climate tech, or anywhere with a compelling story about how you're making the world a better place. I'm comfortable figuring out whatever needs doing and doing it in a small org, but I'm happiest when I get to implement a paper every so often, and when I get to help technical but non-programmer SMEs solve problems they didn't realize could be solved.Remote: Yes
Willing to relocate: No
Technologies: python, numpy/pandas/pytorch ecosystem
Résumé/CV: https://drive.google.com/file/d/1CHWLmjOrw3-Eolc6XX0a2FMWR8u...
Email: matts10e6 at gmail
ML Engineer with 4 years experience. Mostly in computer vision (detection, segmentation, tracking), training and deploying models & coming up with cool uses for foundation models, also some time series analysis. Ask me about how I ended up arguing with a fishing boat captain about neural networks.
I want to build things that people actually use, keep up with the cutting edge of foundation model progress, and maybe publish along the way. Open to all application domains, not just vision. I like learning new things.
But another category of detector [1] adds additional signal by applying a strong, constant electric field vertically across the entire detection chamber (heavy noble gas, not ice, in this case). Then whatever charged particles are produced drift up to the top of the tank, are annihilated there, and you get a flash that gives you extra good localization in the z direction since you know how long it took them to get there.
Which one, out of curiosity? I'm just starting to look into this space and interested in knowing what's out there.
The book you mention seems to cover similar ground: http://www.yorku.ca/eye/toc.htm