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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