Our client is looking for a 🦄 Cloud Engineer to join their team. The team is focused on building a mass-scale, cloud-based media transcoding system. You will help design and build new features, coach and mentor other developers, research innovative technologies, and contribute to enhancements of multi-region and multi-cloud operations.
- Investigate specific customer issues, such as resource contention in a multi-tenant environment, possible defects, and customer-side problems
- Research, design, and implement innovative technologies for improving reliability, efficiency, and performance of the mass-scale cloud-based media transcoding system. Specific areas of focus may include: new efficient architectures for cloud-based media processing and transcoding; segment-based, scene-based, rendition-based, and title based job partitioning schemes; algorithms for efficient aggregation, allocation, and scheduling of transcoding jobs; load estimation and auto-scaling algorithms; optimal multi region and multi-cloud operations; optimal job allocation considering heterogeneous nature of cloud resources such as on-demand and spot-type instances, CPU vs GPU vs FPGA instances; and optimized processing at each worker level including parallel transcoding and optimal pipelining of operations
- Conduct validation studies for proposed technologies and improvements by staging limited scale deployments, collecting metrics, and analyzing results
- Stay abreast of latest developments in cloud platforms, transcoding architectures, new CPU/GPU/FPGA transcoding technologies, new 3rd-party SDKs, open source projects, etc.
- Document and present the results in various forms, such as internal design documents, technical publications, white papers, patent applications, etc.
- 5+ years of hands-on software engineering and architecture experience
- Deep practical knowledge of capabilities and limits of cloud platforms (AWS preferred), including APIs, regions, instance types, and managed services such as auto-scalers, load balancers, storage systems, queues, caches, and lambda functions.
- Experience with relational databases (PostgreSQL/RDS preferred)
- Experience with distributed, in-memory caches (Redis preferred)
- Experience with Ruby and other programming languages
- Experience with Elixir is a plus
- Experience working with Git, TeamCity, CircleCI, Sumo Logic, DataDog, and CloudHealth
- Understanding of building, delivering and operating internet-scale, distributed, high availability systems.
- MS in Electrical Engineering, Computer Science, or related fields
- 5+ years of progressive experience in design and optimization of cloud-based, mass-scale media transcoding, processing, or delivery systems
- Experience with Content Delivery Networks (CDNs)
- Experience with Docker and/or Kubernetes
- Knowledge of system-level standards: HLS, MPEG DASH, CMAF, ISOBMFF, MP2TS, etc.
- Knowledge of structures of payloads and elementary streams: H.264/AVC, HEVC, AAC, AC3, etc.
- Knowledge of means for carriage of subtitles, SCTE35, and other metadata in OTT systems
- Knowledge of deployment guidelines associated with media delivery systems (Apple HLS deployment guidelines, DASH-IF IOPs, DVB-DASH, HbbTV DASH, CMAF content spec)
- Experience using stream analyzers: Sencore CMA 1280, Tektronix MTS, Elecard StreamEye
- Experience working with DRM systems (PlayReady, Widevine, FairPlay)
- Understanding of new and evolving video and audio formats (HDR formats, spatial / object-based audio, immersive systems)
- Experience with forensic watermarking systems
- Experience in GPU or FPGA programming
This is a contract role. And, remote, too (duh!). 🏖️🤘