Senior Machine Learning Engineer - Ad Bidding & Monetization

Reddit is a global community of communities built on shared interests, passion, and trust. Home to authentic conversations across 100,000+ active subreddits and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of human information.

As a Machine Learning Engineer on the Ad Monetization team, you will design, build, and deploy industrial-grade machine learning models to solve high-stakes challenges across ad ranking, automated bidding, and continuous ad delivery optimization. Taking full ownership of the end-to-end ML lifecycle, you will drive offline research, build high-throughput low-latency serving systems on Google Cloud Platform (GCP), design automated retraining pipelines, and engineer features from massive user interaction streams via Kafka. You will also research state-of-the-art algorithms—including Large Language Models (LLMs) and graph architectures—to continuously improve campaign efficiency and monetization performance.

Key Responsibilities

• Ad Ranking & Bidding ML Lifecycle: Take full ownership of industrial-scale machine learning models from ideation, feature engineering, and offline training to real-time serving and operational maintenance.
• High-Throughput ML Serving Systems: Build and maintain scalable, low-latency online inference services and batch data pipelines that handle real-time ad selection and auction bidding.
• Systematic Feature Engineering: Transform raw, heterogeneous user interaction datasets into high-signal features that maximize click-through (CTR) and conversion rate (CVR) predictions.
• Reliability & MLOps Infrastructure: Improve ML platform stability and operational SLOs by constructing robust monitoring tools, real-time alert configurations, and automated model retraining pipelines.
• Advanced Algorithm R&D: Research and deploy modern machine learning techniques—including XGBoost, Large Language Models (LLMs), and Graph Services—to advance Reddit's core ad algorithms.
• Cross-Functional Alignment: Collaborate closely with Product Managers, Data Scientists, and Infrastructure Engineers to convert monetization goals into robust technical execution plans.

Requirements

Education & Technical Experience Depth

• Master’s Degree (or foreign equivalent): Computer Science, Robotics, Engineering (any field), or a related quantitative discipline + two (2) years of professional experience in machine learning engineering or a related technical role.

Special Skill Requirements

1. PII Data Handling: Deep understanding of user privacy safeguards, compliant data governance, and PII data sanitization workflows.
2. Kafka Infrastructure: Hands-on experience working with streaming event-driven architectures and real-time Kafka data ingestion streams.
3. Data Governance: Familiarity with compliance standards, data access controls, and enterprise data lifecycle management.
4. Batch Data Pipelines: Designing, building, and operating high-capacity batch ETL data pipelines for model feature extraction.
5. SLO Management: Constructing systems to meet strict Service Level Objectives (SLOs) around inference latency and service availability.
6. Graph Service Architectures: Working with graph data structures, graph embeddings, or graph network services.
7. Industrial ML Models: Building and deploying deep learning or traditional ML models into high-scale production systems.
8. XGBoost: Applied mastery of gradient-boosted decision trees (XGBoost) for ranking, scoring, or tabular prediction tasks.
9. Large Language Models (LLMs): Practical experience training, fine-tuning, or integrating LLMs into production application workflows.
10. Google Cloud Platform (GCP): Hands-on experience developing ML pipelines and deploying cloud services using GCP tools (Vertex AI, BigQuery, Dataflow).

Total Rewards & Benefits

• Compensation & Equity: Annual base salary range of $216,700.00 – $303,400.00 USD + Restricted Stock Unit (RSU) equity grants + performance/commission incentives where applicable.
• Healthcare & Income Replacement: Comprehensive medical, dental, and vision insurance coverage, gender-affirming care, and income protection programs.
• Financial & Family Support: 401(k) retirement plan with employer match, family planning support, and generous paid parental leave.
• Time Off & Lifestyle: Flexible vacation policy, paid volunteer time off, global workspace and lifestyle stipends, and continuous learning funds.