Reddit is looking for an experienced Staff Machine Learning Engineer 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.
• Own and drive technical roadmaps and lead day to day project execution, and contribute meaningfully to team vision and strategy.
• Make substantial contributions to both immediate wins and long-term objectives through rapid experimentation and iterative processes.
• Mentor junior engineers.
• Work with large scale data, models, piplelines and product integration.

Qualifications:

• 8+ years of industry experience
• 6+ 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.
• MS or PhD degree in Computer Science or related field

Very nice to have!

• 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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