Senior Machine Learning Researcher
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 that 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 validates models during development and monitors these systems in production, helping avoid costly production-time mistakes.
Senior Machine Learning Researcher (Tel Aviv)
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 creating unique methods for determining when models can/can’t be trusted and automatically tackling issues such as: Prediction confidence, overfitting, model monitoring, concept drift, model explanations, and more. In this role, you will be in charge of developing these capabilities, most of which have no “textbook solution”. You will be developing algorithms for a wide range of models and data domains, from tabular to Vision and NLP and will help create robust tools for detecting generic issues with ML model and pipelines. The role also offers the unique opportunity to shape 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.
- M.Sc./Ph.D. in a quantitative field or at least one Kaggle gold medal
- Proven track record of excellence in machine learning
- Python proficiency and solid coding skills
- Product-driven mindset, and ability to contribute to the prioritization process
- At least 4 years of industry experience in ML Research roles
Advantage if experienced with:
- Owning and improving deployed ML systems
- MLOps or AutoML tools (either on the vendor or the customer side)
- XAI, model robustness, or model monitoring
- Unsupervised learning