Senior ML Engineer, Search & Recommendation Relevance

Location:
This role is completely remote-friendly. If you happen to live close to one of our physical office locations, our doors are open for you to come into the office as often as you'd like. 

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Team Description:
The Search & Recommendation Relevance team focuses on delivering the most relevant recommendations when users search for anything on Reddit. Our systems and algorithms operate on the world's largest corpus of human conversation, showcasing the best answers and opinions from all across Reddit on any topics, empowering discovery. 

Role Description:

We are looking for a Senior Machine Learning Engineer to build and iterate on Guides, our next generation AI-driven search product. The person will also be responsible for a seamless integration of Guides into our existing Search Recommendation system. You’ll be responsible for designing and building pipelines and algorithms that make it easy for users to find answers - whether it's recommendations for the best hiking trail, travel advice, or reviews of the next product or restaurant. You’ll work closely with product managers, data scientists, ML modelers and platform engineers to build a state of the search recommender system.

This is a high-impact role where you will be involved in technical & product strategy, operations, architecture, and execution for one of the largest sites in the world.

Responsibilities:

• Contribute to improving Reddit's Search Recommendation Systems and Guides efforts prioritizing seamless and delightful user experience. This involves building out and testing new components in our pipelines, deploying ML models, integrating LLMs, and ensuring effective monitoring and product integration.
• Collaborate across disciplines and with  ML, UX and Infra teams at Reddit to find technical solutions to complex challenges.
• Leverage your technical expertise to ensure our pipelines maintain high uptime and low latency, while collaborating with other technical leaders to develop a long-term roadmap that aligns with the needs of a constantly evolving search product ecosystem.
• Design and develop reproducible ML systems pipelines that coordinate various components to enhance search relevance.
• Champion and drive engineering processes and best practices
• Work with large scale data, models, piplelines and product integration.

Required Qualifications:

• 5+ years of industry experience  as a machine learning engineer or software engineer developing backend / infrastructure at scale.
• Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python, Golang.
• Experienced with GraphQL, REST, HTTP, Thrift or gRPC basics, and the ability to design and implement maintainable APIs.
• Experience working with search & recommender systems and pipelines.
• Deep systems level understanding of industry scale recommendation systems.
• Experience of developing applications using large scale data stack - e.g. Kubeflow, Airflow, BigQuery, GraphQL, Kafka, Redis etc.
  • Big Plus: Experience in working and building machine learning models using PyTorch or Tensorflow.

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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