Machine Learning Engineer, Search (multiple levels)

Posted 23 Hours Ago
Be an Early Applicant
Hiring Remotely in United States
Remote
186K-322K Annually
Mid level
Information Technology • Mobile • News + Entertainment • Social Media
The Role
The Machine Learning Engineer will develop and enhance search retrieval and ranking models, design pipelines for high-quality answers, collaborate with teams to build a recommender system, and ensure system performance and reliability within Reddit's emerging search product ecosystem.
Summary Generated by Built In

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 97M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

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. 
Team Description:
The Search & Recommendation Relevance team focuses on delivering the most relevant results and 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.  

We are looking for Machine Learning Engineers across multiple levels to shape the future of  Search products at Reddit.

In this role, you will contribute to advancing our current search systems as well as building and iterating on Reddit Answers, our next generation AI-driven search product. As a Machine Learning Engineer, you will:

Role Description:

  • Develop and enhance Search Retrievals and Ranking models - from optimizing lexical search (e.g. SOLR tuning) to designing and iterating on semantic models and ranking systems.  
  • Design and build pipelines and algorithms that make it effortless for users to find high-quality answers - whether it's recommendations for the best hiking trail, travel advice, or reviews of the next product or restaurant.  
  • Collaborate with product managers, data scientists, ML modelers and platform engineers to build a state of the search recommender system.
  • Develop and test new components in our pipelines, deploying ML models, integrating LLMs, and ensuring effective monitoring and product integration.
  • 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.  
  • 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. 

Required Qualifications: 

  • 3-10+ years of industry experience as a machine learning engineer or software engineer developing backend / infrastructure at scale. 
  • Experience in working and building machine learning models using PyTorch or Tensorflow.
  • Experience working with search & recommender systems and pipelines.
  • 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. 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.
  •  

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

#LI-DB1 #LI-Remote

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base pay range for this position is:

$185,800$322,000 USD

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at [email protected].

Top Skills

Go
Python
The Company
HQ: San Francisco, CA
1,900 Employees
Hybrid Workplace
Year Founded: 2005

What We Do

Reddit is a community of millions of users engaging in the creation of content and the sharing of conversation across tens of thousands of topics. Our mission is to bring community, belonging, and empowerment to everyone in the world.

Why Work With Us

At Reddit, you’ll help build something that encourages millions around the world to think more, do more, learn more, feel more– and maybe even laugh more.

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