Machine Learning Engineer, Creativex

Amazon Amazon · Big Tech · NY +1 · Software Development

Machine Learning Engineer to join the CreativeX RAPID team, focusing on Dynamic Creative Optimization (DCO). The role involves leveraging generative AI technologies like latent diffusion models, LLMs, RL, and computer vision to tailor ad experiences in real-time with low latency. Responsibilities include investigating new technologies, prototyping, evaluating feasibility, building data pipelines, and developing ML model deployment platforms.

What you'd actually do

  1. Quickly acquire knowledge of nouvelle technologies in Generative AI to solve complex problems in the Dynamic Creative Optimization (DCO) domain.
  2. Investigate design approaches, prototype new technologies, and evaluate their technical feasibility, such as Auto ML, real-time ML serving systems.
  3. Collaborate with scientists to design and build data pipelines for processing massive datasets and scaling machine learning models.
  4. Develop and maintain platforms for developing, evaluating, and deploying machine learning models for real-world applications.

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language

Nice to have

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • latent diffusion models
  • large language models (LLM)
  • reinforced learning (RL)
  • computer vision

What the JD emphasized

  • real-time ML serving systems
  • low latencies

Other signals

  • dynamic creative optimization
  • latent diffusion models
  • large language models
  • reinforced learning
  • computer vision
  • real-time ML serving systems
  • data pipelines for massive datasets
  • scaling machine learning models
  • platforms for developing, evaluating, and deploying ML models