Hi there! We are Tooploox and we work on projects that improve people’s lives - in line with our mission, we have already changed the way people invest their money, build houses and take care of their health (just take a look at our client portfolio). Feel invited!

What you will do:

• Implement both established and state-of-the-art machine learning methods for content analysis, meta-data extraction, content classification, and others
• Work on the algorithms from the idea stage all through to the deployment on production
• Interact directly with various types of clients, from startups to multinational companies such as eBay
• Assure the integrity of project data (data extraction, storage, management, processing, and analysis)
• Work with world-class researchers and scientists to develop new machine learning methods and approaches

Experience and skills you need to join us:

• Team-work attitude with great communication skills
• Software development and coding skills: Python, clean code, code reviews, algorithms and data structures
• Experience with image processing, ML solutions for Computer Vision, classical algorithms for image processing
• Knowledge of machine learning: basic problems in ML modeling, types of modeling, popular models, ways of evaluating the models etc.
• Data-based problem-solving skills, i.e. ability to propose an appropriate tool from either ML, statistics, or software development toolbox to solve client’s problem.
• Basics of statistics: p-value, t-test, confidence interval, correlation, independence of random variables
• Fluency in English (you will attend meetings with English speaking clients).

It would be great if you also have:

• Fluency in deep learning/machine learning libraries: scikit-learn, keras, pytorch, tensorflow, etc.
• Leadership/mentoring experience
• Publication track record in top-tier machine learning/computer vision/natural language processing venues (CVPR, NIPS, ECCV, ICML, ICASSP, ICLR)
• MSc/PhD in computer science, machine learning, signal processing, or related fields