Senior Machine Learning Engineer Core Relevance

Reddit is looking for an experienced Senior Machine Learni

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ng Engineer, Core Relevance to join our ML Core Relevance team. You will execute on our mission to build, productionize and improve large-scale machine learning models for home feed personalization.

You will design and implement ML systems and solutions for rapid content discovery for low-signal users, enable dynamic personalization into our recommendation pipelines, strive to achieve the right balance between exploration and exploitation for our core users. In this role, you will partner with a diverse group of software engineers, product managers, data scientists and other ML modelers. We are excited for you to join our team!

 

Responsibilities:

  • Contribute to enhancing Reddit’s home feed recommendation system and other high-traffic product areas, prioritizing long-term user growth and retention. This involves researching, implementing, improving, testing, and launching new model architectures for candidate retrieval and ranking, such as two-tower, transformer, and graph neural network models.
  • Design and implement content discovery algorithms to connect our users with the most relevant content.
  • Develop and implement algorithms to enhance content distribution within the content and creator ecosystems.
  • Mentor junior engineers.
  • Work with large scale data, models, piplelines and product integration.

 

Qualifications:

  • 6+ years of industry experience
  • 4+ years of experience in building and productionizing end-to-end state of the art candidate retrieval and ranking machine learning models at scale.
  • Deep systems level understanding of industry scale recommendation systems.
  • Proficient in programming languages such as Python, Golang.
  • Proficient in working and building machine learning models using PyTorch or Tensorflow.
  • Big Plus:
  • Experience with large scale data processing & pipeline orchestration tools like Dataflow, Kubeflow, Airflow, BigQuery and Ray.
  • Experience in large-scale deep learning recommendation model training using parallel computing, distributed training frameworks (e.g., Ray Training, PyTorch Distributed), and efficient utilization of hardware resources is a big plus.

 

Benefits:

  • Comprehensive Healthcare Benefits
  • 401k Matching
  • Workspace benefits for your home office
  • Personal & Professional development funds
  • Family Planning Support
  • Flexible Vacation (please use them!) & Reddit Global Wellness Days
  • 4+ months paid Parental Leave
  • Paid Volunteer time off

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