Senior Staff Software Development Engineer - Video Insights (Backend)

Job description

Job Summary: You are a visionary technical leader who thrives in a fast-paced, innovation-driven environment. You have a deep background in machine learning systems architecture and a proven track record of designing scalable AI solutions. You are passionate about advancing the state-of-the-art in video understanding and are eager to lead the architectural vision for our large video models platform. You constantly strive to improve team capabilities and drive technical excellence across the organization. The pace of our growth is incredible – if you want to architect cutting-edge AI systems at scale and create an impact within an entrepreneurial environment, join us! 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: Design and architect scalable ML systems infrastructure for deploying and serving large video models in production environments Define the technical strategy and best practices for model development, evaluation, and monitoring across the team Lead architectural decisions around model selection, optimization, and fine-tuning pipelines for video understanding tasks Collaborate with research and engineering teams to translate complex AI research into production-ready systems Champion adoption of MLOps best practices, including model versioning, A/B testing, and continuous evaluation frameworks Drive performance optimization initiatives to ensure models meet latency and throughput requirements at scale Mentor and guide engineers on architectural patterns, design decisions, and technical trade-offs in AI systems Establish frameworks for model evaluation metrics, benchmarking, and continuous improvement processes Skills and attributes for success: 10+ years of experience in software architecture or systems design, with 5+ years focused on ML/AI systems architecture Deep expertise in designing scalable machine learning systems, including data pipelines, model serving, and inference optimization Strong background in large-scale distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker, Kubernetes) Hands-on experience with modern ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow, Kubeflow, Airflow) Expert-level proficiency in at least one programming language (Python, Java, or C++), with strong software engineering fundamentals Deep understanding of video processing pipelines, codec standards (H.264, HEVC, AV1), and streaming technologies Experience with deploying and scaling video understanding or multimodal AI models in production environments Knowledge of model optimization techniques including quantization, pruning, knowledge distillation, and efficient inference Excellent communication skills and ability to drive alignment across technical and non-technical stakeholders Preferred education and experience: Bachelor's/master's in computer science or a related field with 10-13 years of development experience