🛠 Tech Stack

💼 About This Role

You'll fine-tune large video models for subscription platform monetization, optimizing inference and building evaluation frameworks. Your work will enable seamless, high-retention experiences across millions of users.

🎯 What You'll Do

• Fine-tune large video models using LoRA, QLoRA, and PEFT
• Design and implement model adaptation pipelines for video tasks
• Optimize inference through quantization and distillation
• Build evaluation frameworks and metrics for model quality

📋 Requirements

• 7+ years in machine learning engineering with focus on deep learning
• Advanced Python and deep learning frameworks (PyTorch preferred)
• Experience fine-tuning LLMs and multimodal models with PEFT/LoRA
• Strong understanding of video processing pipelines and streaming

✨ Nice to Have

• MS or PhD in ML/AI
• Experience with CUDA and GPU optimization
• Familiarity with MLOps tools like MLflow or Weights & Biases

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite Interviews· 4 hours

🚩 Heads Up

• Title mentions Senior Staff but requirements ask for 7+ years, not typical for Staff level
• Role mixes ML engineering and MLOps responsibilities
• No salary range provided