Job description
Job Summary
Join our Video Insights team and own high-impact features that leverage cutting-edge video AI. You'll build the systems that transform raw video understanding into real user value, working with large-scale data pipelines, distributed computing, and state-of-the-art ML models. This role offers the unique combination of deep technical challenges and visible user impact.
Be part of a team that's shaping the future of video intelligence for millions of users.
About the team
Join our Video CoE team and own the “face” of our next-generation video intelligence platform. You will build the interfaces that transform raw AI insights into actionable value for millions of users and internal experts alike. This role offers a unique opportunity to work at the intersection of high-scale video streaming, data science, and modern frontend architecture.
Be part of a team that is shaping how users interact with and understand video content globally.
Key responsibilities
Own the end-to-end development of video insights use cases, from requirement analysis through production deployment Design and implement feature pipelines that integrate video AI models with core platform services and data infrastructure Develop robust, scalable solutions for processing large volumes of video content using distributed systems and cloud platforms Collaborate with research scientists, data engineers, and product managers to refine use case specifications and success metrics Build comprehensive evaluation frameworks and dashboards to track feature performance, user satisfaction, and business impact Optimize video processing workflows for performance, cost, and latency while maintaining quality standards Mentor junior engineers and contribute to team knowledge sharing through documentation and technical discussions Drive continuous improvement through monitoring, profiling, and iterative optimization of deployed features Skills and attributes for success: 7+ years of professional software engineering experience, with 3+ years in production ML systems or AI-powered features Expert-level proficiency in at least one of: Python, or C++ with strong software engineering fundamentals Hands-on experience building and deploying end-to-end ML pipelines in production environments Solid understanding of video processing technologies, including codecs, containers, and streaming protocols (HLS, DASH) Experience with large-scale distributed systems, big data platforms (Spark, Hadoop), and cloud infrastructure (AWS/GCP/Azure) Strong foundation in software architecture, system design, and building scalable, maintainable systems Proficiency with data engineering tools and frameworks (Apache Spark, Kafka, Airflow, or equivalent) Understanding of ML fundamentals including model evaluation, feature engineering, and debugging ML systems Experience working with video or image data processing at scale Excellent problem-solving skills and ability to take ownership of complex technical challenges Strong communication skills and ability to collaborate across technical and non-technical teams Preferred education and experience: Bachelors/master's in computer science or a related field with 7-9 years of professional experience BE/B.
Tech in Computer Science, Electrical Engineering, or equivalent. MS or PhD a plus