Staff Machine Learning Engineer (Video Insights)

BengaluruFull Timelead

OtherStaff Machine Learning Engineer

0 views0 saves0 applied

Apply Now

Quick Summary

Overview

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.

Technical Tools

pythonpytorchab-testingdeep-learningmachine-learning

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!

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

6+ 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)

BE/B.Tech in Computer Science, Electrical Engineering, AI, or a related technical field with 7 to 9 Yrs of experience MS or PhD in ML/AI a plus