Video pipelines, codecs, and AI-driven media enhancement at scale Our Mission At Legacybox, we help families reconnect with the most meaningful moments of their lives by digitizing and preserving recorded memories. This role sits at the intersection of: Video pipelines and codecs Hardware + software system design Media processing at scale You will architect and evolve the systems that transform fragile analog media into high-quality digital assets. Technical Focus Areas This role is ideal for someone who has worked with video codecs, media pipelines, FFmpeg‑based systems, or AI‑driven video quality enhancement. Transcoding and format conversion at scale FFmpeg or similar tooling for building and automating pipelines Video quality optimization, including compression and artifact reduction Upscaling and restoration, including super‑resolution and denoising Frame rate conversion and video normalization Color correction and image processing fundamentals GPU‑accelerated processing for video or image workloads Computer vision or AI-based video enhancement (bonus) What You’ll Own Video pipeline architecture and optimization R&D for next‑generation media systems Production systems at scale Video quality and enhancement initiatives Systems economics and performance Tooling and infrastructure Cross‑functional leadership What Success Looks Like Improved video quality and consistency Increased throughput and reliability Successful rollout of new processing systems Better unit economics and efficiency Strong AI‑enhanced media foundation Ideal Background Experience with video processing or media pipelines Strong understanding of codecs and transcoding Hands‑on with FFmpeg or similar tools Experience with GPU processing Background in video/image quality optimization Systems thinker with builder mindset Healthcare coverage that includes medical, dental, and vision plans. Your work will directly impact the quality of service we deliver to hundreds of thousands of families across the country each year as we preserve their most important recorded moments.
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