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Senior Staff Software Development Engineer - Video Insights (Backend)
Bengaluru · Staff/Principal
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What we know about this role
LOW
JioStar is showing limited hiring activity lately. Expect slight delayed response.
First 72 hours
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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:
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:
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
BE/B.Tech in Computer Science, Electrical Engineering, or equivalent. MS or PhD in ML/AI is a strong plus
Excellent communication skills and ability to drive alignment across technical and non-technical stakeholders
Preferred education and experience:
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