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The Spectacles team is pushing the boundaries of technology to bring people closer together in the real world. Our fifth-generation Spectacles, powered by Snap OS, showcase how standalone, see-through AR glasses make playing, learning, and working better together.
We’re looking for a Machine Learning Engineer, CV to join the Computer Vision team in Vienna, Austria!
In this role, you will be working on state of the art machine learning technologies to straddle the boundaries between the real and the virtual world with the next generation of Spectacles. Working from our Vienna office, you will be collaborating closely with other Snap hardware and software teams around the world.
What you’ll do:
- Develop novel technologies for the next generation of Spectacles.
- Explore and advance state-of-the-art machine learning and computer vision algorithms.
- Develop and deploy machine learning models.
- Work together with our cross-functional engineering and research teams in computer vision, machine learning and graphics.
- Deep understanding of machine learning principles, solutions and frameworks to develop networks and models for computer vision tasks
- Ability to understand, debug and improve existing code as well as develop new algorithms using advanced computer vision and machine learning techniques.
- Strong communications and interpersonal skills.
- A genuine passion for learning new things and helping colleagues improve.
- Bachelors’ degree in a technical field such as computer science, mathematics or equivalent experience.
- 2+ years of research or engineering experience with machine learning approaches, in one or more of the following areas: hand/body tracking, object detection, object pose tracking, scene understanding (segmentation, classification), neural scene representation.
- Experience with machine learning frameworks (PyTorch, TensorFlow etc.), as well as with cloud environments (GC, AWS etc).
- Experience with software development in Python or C++
- Msc/Phd in related field (Computer Vision, Machine Learning)
- Experience in integrating Machine Learning models into Augmented Reality solutions
- Experience in geometric computer vision such as SLAM, VIO, Tracking, multi-view 3D reconstruction, Depth Estimation etc.
- Experience in neural network optimization (pruning, quantization, distillation) to deploy efficient models to resource-constrained devices.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
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