Senior Machine Learning Engineer, Reddit

• 5+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models
• Experience building NLP models and integrating them at scale
• Experience with mainstream DL frameworks: TensorFlow or PyTorch
• Excitement about working with data and readiness to look behind the metric numbers

Desirable

• The Ads Contextual Intelligence (ACI) team is responsible for all the “contextualization” projects within the Reddit Monetization charter
• We are in charge of making sense of all user and advertiser-generated content in an automated fashion at scale, providing the right combination of signals to improve marketplace efficiency and bringing to the surface Business Intelligence insights
• Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content
• We are a Machine Learning/Data heavy team with a focus in the following areas:
• Contextual Signals & Relevance - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) content via classification into interpretable tags and embedding into a shared space
• Safety & Suitability - Build in-house classification capabilities for the detection of sensitive & unsafe content in Reddit content to ensure Brand Safety and suitability of ads for users
• Knowledge Graph - Semi-automatic curation, expansion, and utilization of Reddit very own Knowledge database. NLP tokenization, NER models, disambiguation systems at KG node level
• Marketplace Efficiency - Helping Targeting, Retrieval, Ranking, and Marketplace Quality deliver best-in-class performance leveraging our Contextual Signals
• Business Intelligence Applications - Bring Contextual Signals (Web, APIs, Custom Reporting) to Advertisers and other businesses to empower a new generation of Business Intelligence and help Brands understand Reddit bette
• As a Senior ML Engineer, you’ll be in charge of the full cycle execution of content understanding projects - from collaborating with cross-functional teams on requirements and design to the implementation to the experimentation
• Developing new or iterating on existing NLP algorithms and models for advertising use cases, such as NER, text classification, text embedding models, etc
• Building data processing pipelines & APIs that make the signals and annotations computed with those models available
• Hands-on help and consulting for the integration of contextual signals into downstream optimization models (Ad Targeting, Ad Ranking, etc.)
• Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management
• Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance
• Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions