Job Description

Meta's Wearables Media Codec and Framework team develops the video encoding and media capture software that powers wearable experiences. We are looking for a Video Codec Software Engineer to build and optimize codec implementations and hardware-accelerated media pipelines for resource-constrained devices like smart glasses.

In this role, you will own technical problems from camera capture through encoding, media containers, and audio/video synchronization. You will balance compression efficiency, visual quality, latency, power consumption, thermal limits, and memory usage, working across media frameworks, firmware, and kernel drivers. Partnering with camera, hardware, and silicon teams, you will help define the architecture and technical direction of wearable media systems.

Responsibilities

Architect, implement, and troubleshoot video codec and media capture pipelines for wearable devices, from camera capture through encoding and media output

• Develop, configure, and tune video encoders, including rate control and compression algorithms, to improve encoding efficiency and visual quality
• Optimize codec performance within device power, thermal, latency, and memory constraints, using profiling and measurement to evaluate trade-offs
• Integrate hardware-accelerated video codecs with mobile and embedded media stacks, working across application processor frameworks, firmware, and kernel drivers
• Develop and improve media container handling, timestamp management, and audio/video synchronization across the capture and encoding pipeline
• Diagnose and resolve video artifacts, synchronization issues, and performance regressions through codec-level and end-to-end system debugging
• Lead technical design and execution for complex media projects, partnering with camera, hardware, and silicon teams to define interfaces, resolve integration challenges, and guide technical roadmaps
• Build and improve automated tests and regression infrastructure for code correctness, visual quality, performance, and power consumption

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

• Bachelor's degree in Computer Science, Computer Engineering, or relevant technical field
• 7+ years software development experience in industry settings or PhD with 4+ years of experience
• 3+ years relevant video software engineering experience in industry settings with understanding of multimedia stack, codecs, containers
• Experience in C/C++ multithreaded programming
• Experience in C/C++ multithreaded programming
• Experience leading large or complex projects, defined goals and delivered milestones by leading teams Experience with image compression and formats such as JPEG, HEIC/HEIF, or raw/Bayer compression
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience developing automated media regression tests or working with codec tools and libraries such as FFmpeg, libavcodec, x264/x265
• Experience integrating hardware-accelerated video encoding on mobile or low-power systems-on-chip, using media interfaces such as Android MediaCodec, Codec2, OpenMAX, or V4L2
• Knowledge of codec internals, including rate control, motion estimation, intra/inter prediction, rate-distortion optimization, and bitstream analysis
• Experience with media-path firmware or kernel drivers, camera capture integration, or direct collaboration with silicon vendors on hardware-software integration
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience evaluating visual quality using metrics such as PSNR, SSIM, or VMAF, and diagnosing compression artifacts and quality regressions
• Experience with media containers such as MP4/ISOBMFF, muxing and demuxing, timestamp management, and audio/video synchronization
• Experience designing and optimizing media software within power, thermal, latency, and memory bandwidth constraints on wearable, mobile, or embedded devices
• Experience implementing, configuring, or tuning production video encoders using standards such as H.264/AVC, H.265/HEVC, VP9, AV1
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)