roycoding
Joined 13 years ago
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40
Member since
Jun 3
Recent submissions
Comment · 1 year ago
FinQuery | AI Engineer | REMOTE (US) or Atlanta, GA | Full-time
I'm hiring an AI/ML engineer to join the AI/ML team at FinQuery.
Our team creates services powered by LLMs and traditional ML to enable features across our suite of products. Like many companies, we are trying to separate the real value of the latest AI techniques and tools from the hype (agents?), and unlocking use cases that actually benefit our customers. This role is a rather generalist role for someone with a strong ML background, 2+ years of work experience (post schooling), and a desire to work on both proof of concept and production systems. You would be joining our small AI/ML team as we continue to automate as much as possible and enable new product features and use cases.
FinQuery makes software to help companies comply with new lease accounting regulations, manage financial contracts, and keep track of recurring and one-off payments. We're based in Atlanta, but support fully remote employees in the US. This is an IC role.
We are also hiring for roles in DevOps, marketing, and more.
Comment · 2 years ago
LeaseQuery | MLOps Engineer | US remote or Atlanta, GA | Full-time
I'm hiring an experienced (senior, staff, + level) machine learning engineer to lead the tooling, infrastructure, and ops efforts for the ML team at LeaseQuery.
Our team is deploying ML-based services to power features across our suite of products. As we grow the scale and number of our ML-driven features, we are looking to build more robust tools, infrastructure, and ops processes to make our modelers more efficient and our model serving more robust. I'm hoping to find an experienced person that can help us make the best decisions, mentor other team members, and lead the design and implementation of new tools and processes as an IC.
LeaseQuery makes software to help companies comply with new lease accounting regulations, manage their SaaS spend (via our recent acquisition of Stackshine [YC W22]), and more generally handle accounting and spending related to recurring costs. We're based in Atlanta, but support fully remote employees in the US.
https://leasequery.com/careers/
We are also hiring for several roles in software, DevOps, and platform.
Comment · 3 years ago
LeaseQuery | MLOps Engineer | US remote or Atlanta, GA | Full-time
I'm hiring an experienced (senior, staff, + level) machine learning engineer to lead the tooling, infrastructure, and ops efforts for the ML team at LeaseQuery.
Our team is deploying ML-based services to power features across our suite of products. As we grow the scale and number of our ML-driven features, we are looking to build more robust tools, infrastructure, and ops processes to make our modelers more efficient and our model serving more robust. I'm hoping to find an experienced person that can help us make the best decisions, mentor other team members, and lead the design and implementation of new tools and processes as an IC.
LeaseQuery makes specialized accounting software to help companies handle (new) lease accounting requirements and manage their SaaS spend (via our recent acquisition of Stackshine [YC W22]). We're based in Atlanta, but support fully remote employees in the US.
Job ad: https://jobs.lever.co/leasequery/850d1e33-2945-4ab3-aaf2-625...
We are also hiring for several roles in software, DevOps, and product.
Comment · 3 years ago
I published a book last year with a similar goal: Zefs Guide to Deep Learning
It's a pretty short book designed to provide a strong conceptual grounding in the most import ideas in deep learning, starting with an intro to ML. The book posted by the OP appears to be a little more oriented towards the math and people who have a strong grasp of CS theory. I am definitely going to read through it!
I was considering going even smaller and cuter with my actual print book, but ended up with a "pocket book" format that's 5.25" x 8" (13.3cm x 20.2cm) and about 160 pages total. This book seems to get the smallness part down pretty well.
I actually considered the exact same title (The Little Book of Deep Learning) when I started out!
Comment · 4 years ago
I'm about 3/4 of the way through writing my second book right now (Zefs Guide to Deep Learning https://zefsguides.com ). I have am using a somewhat similar workflow. I'm writing in Leanpub's Markua flavor of Markdown, which they use to build ebook, PDF, and HTML formats. They will also produce a reformatted PDF for you for book printing, with appropriate margins.
This is the same thing I did for my first book, except that I want a pocket book size format and there isn't one that both Leanpub and Amazon KDP currently support, so instead I will be doing some LaTeX wrangling to produce a PDF formatted for KDP. I haven't yet decided how I will do that, as there doesn't seem to be a Markua -> Markdown convertor anywhere (pandoc only goes in the other direction).
Comment · 4 years ago
I used to edit the Zim markup directly in a very basic text editor, so Markor is a big improvement. It offers syntax highlighting, some menu items for things like formatting, and a preview mode. So not wysiwyg, but still pretty nice. It also allows you to easily create new notes from scratch, which is kindof a pain if you're just using a generic text editor.
I do have some issues making nested check box lists (maybe I need to review the Zim syntax) and it's not clear if you can add images. Mostly I review and update my todo items, read notes, and write small notes. For that I've been pretty happy with it.
And syncthing is great.
Comment · 4 years ago
I've been using Zim for at least 10 years for notes, todo's, etc.
Recently I updated my setup to use syncthing for syncing between my desktop, laptop, and my Android phone. On my phone I use Markor, an open source app that supports the Zim markup format (along with Markdown and some others). I've been pretty happy with this setup.
Comment · 4 years ago
This is roycoding, the creator of CSVchain. Thanks everyone for checking it out.
Just so you know, I currently have a bit of a backlog of requests to manually process.
This was all very unexpected. I made this recently and then today started getting messages that Matt Levine wrote about something similar in his newsletter today. I tweeted at him and he then tweeted about it to his large following. So here we are on HN!
If you've contacted me, I promise to message you back, but it might take a day or so.
Comment · 5 years ago
OP here
Based on the HN rules, you can't submit a book as a "Show HN", so this is my version of a Show HN, Book Edition.
I've just published the 1.0 version of my book on hiring data scientists and machine learning engineers. There is a ton of material online for people that want to try to get hired as a data scientist or MLE, but very little on how to hire for those roles. Having built and led data science and ML teams at a couple different companies and getting asked by lots of other people about how to hire for these roles at their own companies, I decided to write a book on the subject as my pandemic project.
I first came across data science more than ten years ago on HN and that led me to pivot into a whole new career. So this is sort of a snapshot after nearly a decade working in the industry. The link at the top of this post is for a 50% discount for people coming from HN.
The permanent address for the book is dshiring.com
I'm happy to answer any questions about hiring for these roles (or about writing the book and self publishing).
Comment · 7 years ago
This is my team's second time series related library that we've recently open sourced, the other being https://github.com/arundo/adtk, our anomaly detection toolkit for time series.
We created this library because we were training a lot of deep learning models on time series data, but needed more examples of the specific types of behaviour we were interested in. This data augmentation library is inspired by image data augmentation libraries, but taking the considerations of time series into account. As with image data, you need to carefully consider whether the specific "augmentation" will preserve the aspects of the data that you are interested in.
We've released tsaug under an Apache license. We'd love to have people try it out, make contributions, and ask any questions.
tsaug is pip installable and the documentation and examples are linked in the readme on Github.
Credit primarily goes to Tailai Wen, who led this effort.
Comment · 7 years ago
My team deals with lots of time series data and in particular we are faced with anomaly detection problems on time series. To help us deal with that more efficiently, we built a toolkit in Python, ADTK, to quickly and easily test out different anomaly detection models and data flows.
ADTK has an API that allows you to easily combine a large number of anomaly detection models ("detectors"), data transformers, and ensembling steps ("aggregators") into serial or parallel data flows ("pipelines" and "pipenets"). It can also be easily extended.
We've just recently released ADTK under an open source license (MPL). We'd love to have people try it out, make contributions, and ask any questions.
ADTK is pip installable and the documentation and examples are linked in the readme on Github.
Most of the credit goes to Tailai Wen, who led this effort.
[ my public key: https://keybase.io/roycoding; my proof: https://keybase.io/roycoding/sigs/Ze8CSk0Unuec0WmN4Dkw92flgY1JZVn0HSV_1MBFtLA ]