**Summary**
We have 2.5M labeled data points with 6 TB of time series data. We have a LLM
in production & time series models & recommendations in production with public
companies. We are building the next generation of intelligence to connect time
series models & LLM’s at scale and are looking for someone hungry to join the
team and lead this effort with our CTO.
**About Tasq**
* 4 year old startup
* Focus on being the OS of industry operations. Any industry that has time series data with work needed to be done on a physical asset, is what we can apply to. Our solution continues to prove out 10x ROI per client and we envision automating most of the decisions that need to be made on a daily basis.
* We are around the Series A stage & net income neutral, which is a rarity at our stage.
* Being non VC funded means equity can easily be realized vs very diluted. As our valuation is not too high, this is a great time to get in and own part of the company.
* 15 people. 2 people in sales/client focused, the rest engineers. Headquarters in Denver with flex work (in person & remote).
**Role**
* Build time series models
* Build best-in-class industry LLM for technical intelligence
* Build tools for monitoring model performance
* Package models and deploy to production
* Build endpoints to access model/predictions
* Build ML pipeline from data query to prediction to feedback
* Work on “product led growth” scalable classification model for any time series signals
* Lead ML strategy
**Techstack**
* OpenAI and other LLM development
* RocksetDB
* PineCone
* AWS
* Python
* Coiled
* Polylith
* Github Actions
**Skills & Proficiency**
* Git
* Python Interpreter and Virtual Environment management (venv, pyenv, etc.)
* Python package management (hatch, poetry, etc.)
* Prompting and LLM interactions
* IDE of choice (vscode, neovim, jetbrains)
* Debugging tools
* Python coding standards and practices, including linting / formatting
* AWS infrastructure-as-code frameworks (SAM, CDK, Serverless)
* AWS programmatic API (boto3)
* Docker
* Remote development (ssh)
* Bayesian and Frequentist Statistical Principles and Analysis
**Familiar with**
* Distributed computing or multi-processing/threading frameworks (dask / coiled, joblib, etc.)
* Monorepo design (Polylith)
* Networking principles (DNS, SSL/TLS, Cors, route tables, etc.)
**Time Allocation**
70/30: 70 percent on new models & enhancing current models (research &
testing). 30 percent on architecture, deployment, etc.
Tasq focuses on Oil and Gas. Their company has offices in Denver. They have a
small team that's between 11-50 employees. To date, Tasq has raised $210k of
funding; their latest round was closed on June 2021.
You can view their website at <https://www.tasq.io> or find them on
[Twitter](https://twitter.com/tasqinc) and
[LinkedIn](https://linkedin.com/tasqinc).
