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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 (ML) Platform Engineer to join the Computer Vision team at Snap inc!
What you’ll do:
In this role, you will be supporting the development of cutting edge machine learning technologies for the next generation of Spectacles. Working from our Vienna office, you will be collaborating with other machine learning, computer vision and software teams of Spectacles teams around the world. You will also:
- Own the ML platform to support the training, evaluation and deployment of cutting edge ML models for on-device applications.
- Build data and training pipelines at scale
- Apply strong software engineering to deliver scalable, reproducible end-to-end ML workflows for deep learning and computer vision
- Develop optimization and release toolchain for automated testing/validation, CI/CD for ML, quantization/distillation and packaging
- Drive operational excellence by advocating and applying best practices for scalability and cost management.
- Work together with our cross-functional engineering and research teams in computer vision and machine learning..
- Excellent software design, development and debugging skills in the context of ML systems
- Proven track record of developing highly available systems which deal with large amounts of data
- Working knowledge of ML fundamentals
- Strong communications and interpersonal skills.
- A genuine passion for learning new things and helping colleagues improve.
- Ability to travel as needed
- Bachelors’ degree in a technical field such as computer science or equivalent experience.
- 4+ years of relevant industry experience
- Experience with Python, C++ or equivalent combined with a proven track record of learning on the job
- Experience with machine learning platforms and infrastructure
- Experience building large scale production machine learning systems or data pipelines
- Experience with Docker, Kubernetes, Istio/Envoy, NoSQL solutions, Memcache/Redis, Google/AWS services
- Experience with Tensorflow, PyTorch, or related deep learning frameworks
- Experienced in MLOps: managing production machine learning lifecycle
- Familiarity with Metaflow, Airflow, Kubeflow or similar workflow orchestration framework
"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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