DEEP LEarning Scientist
Work on some of the most sophisticated problems in your field.
At Vtrus we are enabling a future where devices can socially collaborate, perceive and learn like humans using cloud-based spatial AI.
As a machine learning scientist we expect you to architect our core perceptual stack enabling our devices to remember where they were, interpret and predict human communication, as well as learn new robotics control strategies.
This exciting position is within the first layer following the founding team and as such it offers one of the most rewarding experiences in helping to orchestrate and nurture the development of a world-class technical team, as well as the ability to take part in key company-wide decisions. Your responsibilities and commitment will be rewarded with generous stock options and competitive salary.
At Vtrus we reward and encourage scientific publications and facilitate activities to remain active in the academic community.
- PhD in computer science or related areas.
- 2+ years of experience within a commercial or academic environment.
- Publications in renowned conferences and journals (NIPS, ICCV, CVPR, etc).
- Desire to lead a technical team.
- Hands on attitude: being able to lead a team whilst getting involved in prototyping, designing experiments or writing new software.
- Solid mathematical background.
- Understand the principles behind Simultaneous Localization and Mapping (SLAM).
- Scalable place recognition and camera relocalization from RGBD cameras.
- Human motion estimation from RGBD and monocular cameras.
- Novel machine-learning approaches for robotics control.
- In-depth expertise and tradeoff in applying a variety of learning techniques such as Forests, SVM, Neural Networks, Reinforcement Learning.
- An interest in designing robust and scalable system architectures alongside top engineers.
- Comfortable programming with Matlab, Python, C#, C/C++.
- Dynamic, pet-friendly atmosphere with spectacular views over the Salmon Bay in Seattle
- Discounted gym membership
- Competitive salary
- Flexible working hours
- $90K-$150K salary according to experience
- 0.5%-5% stock options according to experience
To apply, please email firstname.lastname@example.org with your full name, phone number, and resume. We look forward to hearing from you!