Work closely with deep learning engineers and tech leaders across the company, demonstrating flexibility and effective communication in a global, multi-time-zone environment.

Supervise complex data pipelines, from the collection stage, through annotation, to models training.

Design and optimize deep neural networks, involving innovative feature engineering.

Take an End-to End responsibility over medium to long-term projects

See projects through from research to deployment.

Devise and implement performance metrics.

Communicate, present and visualize results.

Align the algorithms with the product needs.

M.Sc. or equivalent work track experience in CS, EE, Physics, or other quantitative field from a leading university. Ph.D. – Advantage

A proven track record of at least 3 years hands-on experience in developing deep learning algorithms.

Experience and knowledge in computer vision and image processing algorithms, including classification, object detection, and/or semantic segmentation

In-depth, hands-on knowledge of deep learning fundamentals.

Hands-on experience with deep learning frameworks such as PyTorch.

Strong mathematical aptitude, with emphasis on probability, vector algebra, and geometry.

Proficiency in Python programming.

Experience in conducting long-term development and/or research projects, in either academia or industry.

Proficiency in English, both written and spoken.

Team player – fosters a positive and cooperative work environment by maintaining strong collaboration within the team and building productive relationships with other teams across the company

Eligible to work in the US

Skills That Are Considered An Advantage Publications in top-tier journals or conferences on algorithms, computer vision, or deep learning

Basic proficiency in C++

Experience with Linux

Source control with git

Salary range: 170-190 K annually.