As machine learning systems begin to transition from the research phase to the production phase, it’s becoming clear that they have unique QA and testing-related challenges.
Deepchecks offers a customizable, plug & play, algorithm-based solution, for testing and monitoring machine learning systems.
Deepchecks is a VC-backed startup tackling the huge problem of controlling Machine Learning systems.
AI systems are being adopted by more and more organizations and are taking an increasingly important role in their business. Although many resources are allocated to creating and optimizing the machine learning models, they still lack “common sense” and make various mistakes which may go undetected for long periods of time. We focus on detecting, preventing, and fixing these “AI glitches”, using mathematical concepts and algorithmic research. Our product monitors these systems in production, identifies a wide range of potential problems, and offers different types of alerts and explanations (depending on the type and the severity of the issue).
The startup was founded by two Talpiot graduates / Data Scientists and a leading professor in this field. Following a few months of R&D and initial customer traction, the time has come to expand our extremely talented (and fun!) team. Our offices are in Tel-Aviv, although we’ve recently been working from home most of the time.
We’re looking for a top-notch Machine Learning Researcher, that has both broad experience with Data Science (i.e. experience with various types of models and tasks), and solid coding skills. We’re developing unique methods for determining when models can/can’t be trusted, and automatically tackling issues such as: Prediction confidence, overfitting, model monitoring, concept drift, counterfactual explanations, and more. In this role you will play a central part in developing our core algorithms used for solving these problems, as well as shaping our product from a user’s point of view.
We’ll be going through a lot together, so we’ll want your character and mindset to be a good fit for a fast-moving startup.