9 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Own end-to-end development of video insights use cases from requirements analysis through production deployment.
- Design and implement feature pipelines integrating video AI models with platform services and data infrastructure.
- Build scalable distributed systems for processing large volumes of video content on cloud platforms.
- Collaborate with research scientists, data engineers, and product managers to define use cases and success metrics.
- Develop evaluation frameworks and dashboards measuring feature performance, user satisfaction, and business impact.
- Optimize video processing workflows for performance, cost, latency, and quality.
- Monitor, profile, and iteratively improve deployed features.
- Mentor junior engineers and contribute to documentation, technical discussions, and knowledge sharing.
Requirements
- 7+ years of professional software engineering experience, including 3+ years building production ML systems or AI-powered features.
- Expert proficiency in Python or C++ with strong software engineering fundamentals.
- Hands-on experience building and deploying end-to-end ML pipelines in production.
- Experience with video processing technologies, including codecs, containers, HLS, and DASH streaming protocols.
- Experience with large-scale distributed systems, Spark, Hadoop, and cloud infrastructure such as AWS, GCP, or Azure.
- Proficiency with data engineering tools and frameworks including Apache Spark, Kafka, or Airflow, or equivalent technologies.
- Understanding of ML fundamentals including model evaluation, feature engineering, and debugging ML systems.
- Experience processing video or image data at scale.
- Strong software architecture, system design, problem-solving, ownership, communication, and cross-functional collaboration skills.
- Bachelor's or master's degree in computer science or a related field, or a BE/B.Tech in Computer Science, Electrical Engineering, or an equivalent qualification; MS or PhD is a plus.
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