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
