Software Engineer, ML & Search Infrastructure (multiple levels)

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. 

We are hiring Machine Learning Infrastructure Engineers for multiple levels across the following teams:

ML Search Infrastructure:
The Search Infra team manages the Search Retrieval Infra & Platform at Reddit, crafting and maintaining the essential databases, interfaces & services that ensure users find what they’re looking for quickly and accurately. With a focus on building robust machine learning infrastructure, we prioritize reliability and performance, enabling seamless search experiences across the platform. We are collaborating closely with a team of machine learning engineers and backend architects to develop the next generation of search infrastructure at Reddit, enabling a variety of search functionalities, including Vector and Lexical search.

ML Ranking Platform:
Ranking is a core and growing part of Reddit, connecting users with the content they’re looking for is key to the future of Reddit. This is particularly salient right now, as our society is currently engaging in a deep discussion around the algorithms used to match users with content. The ML Ranking Platform team builds and runs the services that coordinate contextualized and personalized ranking on Reddit. We build ML infrastructure, including a scatter-gather ranking coordination service and feature indexes. We are deeply concerned with helping our users fulfill their intention for visiting Reddit, not just capturing their attention.

AI Serving Infrastructure:
The AI Serving team develops and maintains Reddit's high-performance model serving infrastructure, generating millions of model predictions per second with low latency. We collaborate closely with machine learning engineers to support a diverse range of models and partner with training and feature teams to deliver a seamless train-to-serve experience for efficient and reliable model deployment

As a Machine Learning Infrastructure Engineer on any of our teams, you will be responsible for designing, building, and maintaining the infrastructure and platform that powers our search capabilities. You will collaborate with Backend Architects and Product ML teams to shape the roadmap for ML infrastructure and platforms, while providing ongoing support to scale the platform and meet evolving needs for state-of-the-art models.

How You'll Have Impact
You will build systems and tools that enable machine learning engineers (MLEs) and data scientists (DSs) and continuously improve the ML software development lifecycle, enabling the continuous iteration and improvement of systems that use ML techniques, including Deep Learning, Natural Language Processing, Recommendation Systems, Representation Learning, and Computer Vision.

• Lead the building, testing, and maintenance of ML infrastructure at Reddit
• Propose, design, and implement high-performance ML Infra solutions that significantly advance the deployment of models that serve millions of redditors a seamless experience for MLEs
• Design and implement solutions that significantly advance the ML Infrastructure
• Collaborate closely with XFN partner teams/internal customers.
• Work with management on team goal setting, planning, and de-risk project execution
• Mentor other team members in adopting a rigorous DevOps approach to maintain and/or improve ML infra components and services health and quality

Who You Might Be:

• 3-8+ years of work experience in a production software development environment
• Experience working on large-scale ML Systems
• Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in golang, Python and Scala.
• Experience with Kubernetes
• Knowledge of maintaining or developing applications using large-scale data stack, e.g, BigQuery, GraphQL, Kafka, Flink, Cassandra, Redis, Search Databases 
• Comfortable with distributed systems, big data (Petabyte scale) and data-intensive systems
• Strong organizational & communication skills

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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