Machine Learning Research Engineer

Job description

We are building MindsDB, an open-source explainable AutoML tool. We want to give everyone the ability to make informed predictions, using state-of-the-art ML models, with just a few lines of code.

We're looking for Machine Learning experts to join us in the journey of bringing state of the art Machine Learning to everyone.


You will be part of our Machine Learning team, with a focus on designing and implementing end-to-end Machine Learning workflows, we have a strong focus on explainability, so a lot of the work you will be doing will involve making sure that the Machine Learning models that our system generates, can explain to all (including non-technical people) where they should and should not trust the model when the model predict something, why are they making such predictions and to understand what within the data used should be of interest.

Since our project is Open Source, we encourage you to take a look at it: https://github.com/mindsdb/mindsdb & https://github.com/mindsdb/lightwood.


Requirements

You are confident that you can solve the following challenge:

https://github.com/mindsdb/lightwood/issues/169


We are looking for a team member that is:


* Eager to understand things and experiment
* Good at working with minimal supervision in a remote environment
* Excited by discussing, deconstructing and challenging ideas
* Good at communicating in English, don't worry, you don't need to be a native speaker or a poet.

* Enjoys and can be confident at programing in Python 3 


Qualifications:
* Strong understanding of machine learning and artificial neural networks, for example through active research in a
related PhD program or experience in research labs.
* Experience working with Pytorch is required.
• Papers in academic conferences (NeurIPS, ICML, ICLR, AAAI or domain-specific conferences).

Most important of all, is that you actually like MindsDB and believe in what we are trying to accomplish. We want to democratize Machine Learning and we want to make it explainable, most ML solutions out there focus on just making predictions, we also focus on the question:

* What is interesting in my data and why?
* When should I not trust this model and why?
* How can I improve this model?
* Why did the model give this prediction?

MindsDB is an equal opportunity employer. All qualified applicants will receive consideration for
employment without regard to age, ancestry, color, family or medical care leave, gender identity or
expression, genetic information, marital status, medical condition, national origin, physical or mental
disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual
orientation, or any other characteristic protected by applicable laws, regulations and ordinances.