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The XR team at Facebook Reality Labs is helping people around the world come together and connect through world-class Augmented and Virtual Reality technologies.
As a Software Engineer for XR Streaming, you will be taking a lead in developing streaming technologies for cloud rendering to enable cutting edge visual experiences on compute constrained AR/VR devices.
You will work with a highly cross-functional team to define an end-to-end streaming solution to achieve ultra low latencies and a smooth streaming experience.
Software Engineer - XR Streaming / Networking (Tel Aviv) Responsibilities
Develop local and cloud based ultra-low latency game and app streaming technologies
Innovate in the areas of Video Streaming, QoS and transport/networking to achieve breakthrough streaming metrics for quality, latency and stutter
Research, develop, innovate new software algorithms across the end to end streaming pipeline. Collaborate closely with partner teams to innovate across the entire end to end software and hardware technology stack

Meta is embarking on the most transformative change to its business and technology in company history, and our Machine Learning Engineers are at the forefront of this evolution. By leading crucial projects and initiatives that have never been done before, you have an opportunity to help us advance the way people connect around the world.

The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems. You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. You will work alongside the worlds leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.
Software Engineer, Machine Learning Responsibilities
Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
Adapt standard machine learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
Leading a team from a technical perspective to develop ML best practices and influence engineering culture
Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmap
Code deliverables in tandem with the engineering team