Job description
Remote, United States
Video Encoding and Streaming
Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.
Among other functions, Open Connect provides highly available infrastructure for content production, processing, and distribution across all Netflix productions and licensed content. As part of this, we are working on new ways of delivering entertainment that requires real-time, ultra low-latency network transport technologies.
We are looking for a senior software engineer with experience designing RTP/RTCP-based solutions for delivering highly-interactive, ultra-low latency streaming over internet service provider networks world-wide. You understand the dynamic nature of internet paths, and how they impact interactive media streams. You will refine and improve today's state-of-the-art heuristics for rate & latency estimation, congestion control and loss recovery for RTP-based media streams. You will collaborate with colleagues to implement and deploy your new ideas into our server-side, real-time transport stack. You will work closely with server, client and data analytics colleagues to evaluate and refine your designs using a mix of lab and production (A/B) testing. All of this excites you.
In this role, you will have the opportunity to directly impact an emerging area of business. We provide the freedom to execute, learn and pivot, and the responsibility to be self directed, collaborative and insightful.
Qualifications:
- Deep understanding of modern strategies for balancing network congestion, goodput, latency and reliability in support of interactive, ultra low-latency, RTP-based streaming.
- Familiarity with how low-latency, two-way media flows over IP networks interact with bufferbloat, active/smart queue management, and concurrent TCP-like traffic.
- Experience using network lab environments for controlled data networking experiments exploring large, multi-parameter test spaces. Experience using A/B testing methodologies for transport stack performance testing in production.
- Practical understanding of Secure RTP/RTCP, DTLS, SCTP, STUN/TURN and ICE protocols.
- An ability to articulate for diverse audiences the technical and business implications of performance measurement experiments executed both in the lab and in production.
- Experience partnering with remote engineering or product teams across multiple time zones.
- Experience with software development in Linux or closely-related environments.
- Experience with tcpdump/wireshark, python and R (or similar tools) for network traffic capture, test orchestration, post-capture analysis and presentation.
You will be successful in this role if you:
- Have the ability to define and self-manage cross-functional projects fueled by ambiguous questions.
- Are a self-starter, curious and not afraid to ask when in doubt.
- Are a quick learner and excited about learning new technologies.
- Advocate software craftsmanship, take pride in your work and enjoy taking full ownership of projects from conception to production.
Nice to have:
- Masters or Bachelors degree in a relevant science or engineering discipline.
At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
The overall market range for roles in this area of Netflix is typically $300,000 - $900,000
This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.
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