Senior Staff Machine Learning Engin...

As a Senior Staff Machine Learning Engineer specializing in Video Insights at JioStar in Mumbai, Maharashtra, you will be an integral part of the Video CoE team. This role demands strong independence, technical expertise, and collaborative spirit to deliver high-quality, timely projects. You will serve as a functional lead, guiding team members in the domain of multimodal AI and video understanding.

You will work with cutting-edge multimodal AI technology, focusing on fine-tuning and optimizing large video models (Vid-LLMs) using advanced techniques like LoRA, QLoRA, and PEFT. Your responsibilities include designing and implementing efficient model adaptation pipelines for domain-specific video content and use cases, optimizing model inference through quantization and knowledge distillation, and conducting extensive experimentation to identify optimal model configurations.

Building robust evaluation frameworks, collaborating with research and product teams to translate business needs into model tuning objectives, and documenting methodologies are key aspects of this role. You will also contribute to open-source projects and stay abreast of the latest advancements in multimodal AI and video understanding. This is an opportunity to tackle complex ML challenges at scale and make a significant impact within an entrepreneurial environment.

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 a 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 years of experience. MS or PhD in ML/AI is a plus.