Computer Vision 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.
Computer Vision Researcher (Tel Aviv)
Deepchecks is expanding its product and open-source package into validation and monitoring of Computer Vision (CV) models and data. For that, we’re looking for a top-notch CV researcher to join this effort – someone with experience researching and developing models for various computer vision tasks, along with great coding skills. In this role, you’ll be creating unique methods for detecting flaws in CV models and tackling issues such as prediction confidence, overfitting, model monitoring, concept drift, model explanations, and more. You’ll be taking a prominent role in developing Deepchecks’ offering for CV models, alongside participating in the development of robust tools for detecting generic issues with ML model and pipelines in a wide variety of additional models and data domains. 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
- At least 2 years of industry experience in ML Research roles, at least 1 year out of them developing computer vision models.
- 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
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