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Creatify

Machine Learning Engineer

Mountain View$190k–$300kfulltimemidAdded 1 month ago

About this role

Creatify is seeking a Machine Learning Engineer to design and scale advanced models for their AI-powered video advertising platform. You'll work on large-scale ML problems involving prediction, recommendation, and generative AI while mentoring junior engineers and occasionally leading projects.

What you'll do

  • Design and develop scalable ML systems for prediction, ranking, recommendation, and generative AI problems
  • Research and implement state-of-the-art approaches including LLMs, transformers, and diffusion models
  • Build and optimize large-scale systems leveraging deep learning and modern parallel environments (GPUs, distributed clusters)
  • Identify bottlenecks and synthesize requirements across technology, systems, and tools
  • Mentor junior engineers and lead small teams or projects with technical guidance and architectural direction
  • Iterate quickly on solutions that efficiently scale to handle massive data volumes

What they're looking for

  • Machine learning (deep learning, transformers, LLMs, diffusion models)
  • Large-scale system design and optimization
  • Python and software engineering best practices
  • Distributed computing and GPU acceleration
  • Applied ML domains (ranking, classification, recommendation, fraud detection)
  • Technical leadership and mentoring
  • Production ML systems and deployment
  • Data analysis and algorithm development
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Creatify

Creatify builds an AI-powered video advertising platform that automates ad creation and optimization across social platforms for millions of users. The company is hiring full-stack engineers, machine learning engineers, AI research engineers, and interns to develop its backend systems, frontend interfaces, advanced ML models, and cutting-edge generative AI capabilities.

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Likely interview questions

  • Describe a large-scale ML system you've built in production. What were the main bottlenecks, and how did you optimize for latency and throughput?
  • Tell us about your experience with generative AI or foundation models (LLMs, transformers, diffusion). How have you applied them to solve real problems?
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