Principal Software Engineer, Video Engineering

Who we are

At Twelve Labs we are pioneering the development of cutting-edge multimodal foundation models that have the ability to comprehend videos just like humans do. Our models have redefined the standards in video-language modeling empowering us with more intuitive and far-reaching capabilities and fundamentally transforming the way we interact with and analyze various forms of media.

With a remarkable $107 million in Seed and Series A funding our company is backed by top-tier venture capital firms such as NVIDIAs NVentures NEA Radical Ventures and Index Ventures and prominent AI visionaries and founders such as Fei-Fei Li Silvio Savarese Alexandr Wang and more. Headquartered in San Francisco with an influential APAC presence in Seoul our global footprint underscores our commitment to driving worldwide innovation.

We are a global company that values the uniqueness of each persons journey. It is the differences in our cultural educational and life experiences that allow us to constantly challenge the status quo. We are looking for individuals who are motivated by our mission and eager to make an impact as we push the bounds of technology to transform the world. Join us as we revolutionize video understanding and multimodal AI.

About The Role

Most video engineering roles at Netflix YouTube or Twitch optimize for human playback better compression lower bitrate smoother streaming. At Twelve Labs video is processed for machine understanding. The tradeoffs are fundamentally different: we optimize for AI model performance not just perceptual quality. This is a rare opportunity to define how video is engineered for intelligence not just delivery.

As the Principal Software Engineer Video Engineering you will own the architecture and implementation of Twelve Labs video processing pipelines from byte ingestion through decode chunking storage and playback ensuring it is fast cost-efficient and purpose-built for AI-native video intelligence at scale. You will be the internal subject matter expert on all things related to video engineering.

In This Role You Will:

• Own the video pipeline end-to-end: Architect and implement ingestion decode chunking storage retrieval playback across batch and streaming modes based on AI/ML workflows or media application workflows.

• Deep codec & decode mastery: Drive decisions on decode strategies (hardware vs. software GPU-accelerated pipelines) container format handling (fMP4 CMAF MKV TS) and codec support (H.264 H.265 VP9 AV1) with pragmatic cost/quality tradeoffs.

• Semantic & heuristic chunking: Work with our ML Research Scientists to design and implement intelligent video segmentation that goes beyond fixed-interval splitting scene boundary detection shot change analysis content-aware chunking that optimizes downstream AI model performance.

• Streaming ingestion: Architect low-latency streaming pipelines (HLS DASH LL-HLS WebRTC ingest) that process video in near-real-time including streaming decode and incremental chunking.

• Video storage architecture: Design storage tiers and retrieval patterns optimized for AI workloads balancing hot/warm/cold access frame-level random access and cost at petabyte scale.

• Playback & delivery: Ensure video can be served back to users with accurate temporal navigation supporting time-coded references from AI analysis results.

• FFmpeg & media toolchain expertise: Be the internal authority on FFmpeg libav and related tooling. Build and maintain custom processing pipelines filters and integrations.

• Cost engineering: Quantify and optimize cost-per-hour-of-video-processed. Drive decode efficiency through hardware acceleration (NVDEC VA-API) pipeline parallelism and intelligent resource allocation.

• Cross-team technical leadership: Partner with ML teams on how video is preprocessed for model consumption with platform teams on infrastructure and with product on customer-facing media capabilities.

• Standards & best practices: Establish video engineering standards author reference implementations and mentor engineers across teams on media fundamentals.

You May Be A Good Fit If You Have:

• 12 years in software engineering with 7 years focused on video/media engineering in production systems processing video at scale.

• Deep FFmpeg expertise: Not just CLI usage understanding of libavcodec libavformat filter graphs custom demuxers/decoders and performance tuning.

• Codec internals knowledge: H.264/H.265 bitstream structure AV1 adoption tradeoffs hardware decode paths quality metrics (VMAF SSIM PSNR).

• Streaming protocol fluency: HLS DASH LL-HLS WebRTC. Experience with live/real-time ingest pipelines.

• Systems engineering depth: Comfortable in C/C Rust or Go for performance-critical media code; Python for pipeline orchestration. Can reason about memory layout SIMD GPU pipelines.

• Storage & retrieval at scale: Experience designing video storage systems object stores frame-indexed access patterns tiered storage strategies.

• Content-aware processing: Experience with scene detection shot boundary analysis temporal segmentation or perceptual quality optimization.

• Production instincts: Incident response observability for media pipelines debugging decode failures at scale handling format edge cases gracefully.

• AI/ML integration experience (strongly preferred): Worked with teams consuming video frames for model training/inference. Understands how preprocessing decisions (resolution frame rate chunking strategy) impact model quality.

Qualified Candidates May Also Have:

• Made major contributions to FFmpeg GStreamer or open-source media projects.

• Deep familiarity with GPU-accelerated video processing (ex. NVDEC/NVENC).

• Experience running media pipelines in constrained environments such as on-prem or edge settings.

Candidates must be able to travel up to 10% of the time annually to attend conferences off-site meetings and other business-related events as required by the role. This role may require participation in on-site interviews and/or completion of in-person onboarding processes.

Benefits and Perks

An open and inclusive culture and work environment.

Work closely with a collaborative mission-driven team on cutting-edge AI technology.

Full health dental and vision benefits

Extremely flexible PTO and parental leave policy. Office closed the week of Christmas and New Years.

VISA support where applicable

Required Experience:

Staff IC