At Reddit, we work hard to earn our users’ trust every day. Safety Engineering org diligently defends Reddit’s integrity by fighting spam, abuse, bots, and fraud. Our team members are motivated to find innovative, state of the art solutions, leveraging ML models, data systems and user insights to pursue the highest possible quality and safety standards for users across our products.

As a Machine Learning Engineer on our Safety Signals team, you will be in charge of designing and building scalable and accurate ML systems to detect and mitigate safety violations across the Reddit platform. You will be deeply involved in the technical details of building highly available and real-time risk detection services in close collaboration with product, data science and operations teams to understand ever evolving attack vectors and to keep Reddit a safe and trusted community.

If ensuring the safety of users on one of the most popular websites in the US excites you, then you’ve found the right place. We’re a small, tightly-knit company with one of the highest user: employee ratios in the industry, giving you a tremendous opportunity for both scope and impact.

Responsibilities:

• Architect and deploy sophisticated Machine Learning models to detect evolving attack vectors.
• Increase efficiency through automation, improved signals, and system optimization.
• Participate in the full development cycle: design, develop, QA, experiment, analyze, and deployment.
• Collaborate across disciplines and with other ML teams at Reddit to find technical solutions to complex safety challenges.

What We Can Expect From You:

• 4+ years of industry experience as a Machine Learning Engineer in a production-based environment (Trust & Safety preferred).
• Capacity to cover the entire ML lifecycle, including data curation, modeling, productionization (i.e., feature engineering, online inference, service integrations) and A/B Testing.
• Up to speed on industry best practices in Machine Learning.
• Preferred ML experience in Safety moderation, image classification,  or NLP.
• Preferred experience with Sklearn, Tensorflow or Keras. 
• Experience with extracting insight from data (SQL preferred) and writing production-quality software (Python preferred).
• Able to communicate and discuss complex topics with technical and non-technical audiences.
• Passion for delivering products end-to-end, from ideation through planning and scoping to implementation and experimental A/B testing.