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Senior Staff Machine Learning Engineer (Video Insights)

Jiostar · Bengaluru, Indien · On-site

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Description

Job Summary: As a Staff Machine Learning Engineer, you will demonstrate strong independence and technical proficiency while collaborating effectively within the team. You will uphold a standard of excellence, ensuring high-quality work and timely delivery of projects. Additionally, you will serve as the functional lead within your domain, providing guidance and expertise to team members.
About the team: Join our Video CoE team as a Senior ML Engineer focused on fine-tuning and optimizing large video models. You'll work with cutting-edge multimodal AI technology, experimenting with the latest video understanding models and customizing them for real-world use cases. Your work will directly impact millions of users by enabling smarter video insights and content understanding. Be part of a team that combines deep ML expertise with the infrastructure to deploy at scale.  
 
Join our cutting-edge technology team focused on advancing video understanding through custom-tuned large video models. If you want to tackle hard and interesting ML problems at scale and create an impact within an entrepreneurial environment, join us! 

Key responsibilities:

  • Fine-tune large video models (Vid-LLMs) using advanced techniques such as LoRA, QLoRA, and PEFT for specific video understanding tasks
  • Design and implement efficient model adaptation pipelines for domain-specific video content and use cases
  • Optimize model inference performance through quantization, knowledge distillation, and hardware-specific optimizations
  • Conduct extensive experimentation and ablation studies to identify optimal model configurations and hyperparameters
  • Build robust evaluation frameworks and metrics to assess model quality, generalization, and edge case performance
  • Collaborate with research and product teams to translate business requirements into model tuning objectives
  • Develop and maintain documentation of tuning methodologies, lessons learned, and best practices for the team
  • Contribute to open-source projects and stay current with the latest advancements in multimodal AI and video understanding

Skills and attributes for success:

 
  • 7+ years of professional experience in machine learning engineering, with specific focus on deep learning and model fine-tuning 
  • Advanced proficiency in Python and hands-on experience with deep learning frameworks (PyTorch preferred)
  • Hands-on experience fine-tuning large language models and multimodal models using PEFT, LoRA, and similar techniques
  • Strong understanding of video codecs, video processing pipelines, and streaming technologies
  • Solid foundation in computer vision and deep learning fundamentals (CNNs, Transformers, attention mechanisms)
  • Experience with model evaluation frameworks, A/B testing, and continuous experimentation infrastructure
  • Proficiency with GPU-based training and inference optimization using CUDA or similar frameworks
  • Excellent problem-solving skills and ability to debug complex ML systems in production
  • Experience with version control (Git) and MLOps tools (MLflow, Weights & Biases, or similar)

    • Preferred education and experience:

  • BE/B.Tech in Computer Science, Electrical Engineering, AI, or a related technical field with 9 to 12 Yrs of experience MS or PhD in ML/AI a plus 

    • Additional Information

    About Us
    Perched firmly at the nucleus of spellbinding content and innovative technology, JioStar is a leading global media & entertainment company that is reimagining the way audiences consume entertainment and sports. Its television network and streaming service together reach more than 750 million viewers every week, igniting the dreams and aspirations of hundreds of million people across geographies.

     JioStar is an equal opportunity employer. The company values diversity and its mission is to create a workplace where everyone can bring their authentic selves to work. The company ensures that the work environment is free from any discrimination against persons with disabilities, gender, gender identity and any other characteristics or status that is legally protected.