JioStar
media & entertainment
StaffMachineLearningEngineer(VideoInsights)
Neural analysis suggests this role is
optimal for Staff candidates.
“Staff Machine Learning Engineer (Video Insights) at JioStar. Skills: Fine-tune large video models (Vid-LLMs), LoRA, QLoRA, PEFT, model adaptation pipelines, model inference performance optimization, Python, PyTorch, large language models, multimodal models, computer vision, deep learning fundamentals. 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”
What You'll Achieve.
high-quality work; timely delivery of projects; seamless onboarding; high retention; reliable payments at scale
Industry & Context.
Excellent problem-solving skills; ability to debug complex ML systems in production
What They're Looking For.
Must Have
6+ years of professional experience in machine learning engineering, specific focus on deep learning and model fine-tuning, Advanced proficiency in Python, 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, 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 testing, and continuous experimentation infrastructure, Proficiency with GPU-based training and inference optimization using CUDA or similar frameworks, Excellent problem-solving skills, ability to debug complex ML systems in production, Experience with version control (Git), MLOps tools (MLflow, Weights & Biases, or similar)
Nice to Have
MS or PhD in ML/AI a plus
What You'll Do.
Fine-tune large video models (Vid-LLMs) using advanced techniques such as LoRA
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
and edge case performance
Develop and maintain documentation of tuning methodologies
and best practices for the team
Contribute to open-source projects
stay current with the latest advancements in multimodal AI and video understanding
How You'll Work.
Team & Collaboration
collaborating effectively within the team; Collaborate with research and product teams
Full Job Description
## Description Job Summary: As a Staff Software 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: Subscriptions and Payments Team powers the end-to-end direct monetization engine for India’s largest subscription platform, with over 250M+ subscriptions. We build scalable, multi-tenant systems for acquiring users via D2C and partner channels, reducing churn through intelligent renewal and retry mechanisms, and integrating deeply with global and local payment ecosystems like UPI Autopay and card mandates. Our platform drives seamless onboarding, high retention, and reliable payments at scale—enabling frictionless subscription experiences across geographies and devices. ## 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 6+ years of profess
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