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Senior Staff Software Development Engineer - Video Insights (Backend)

JioStar
Bengaluru, IND
Senior · 10+ years experience
Onsite
Discovered 2 weeks ago

Full Job Posting

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

Qualifications

  • Hands-on experience with modern ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow, Kubeflow, Airflow)
  • Experience with deploying and scaling video understanding or multimodal AI models in production environments

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