Enhance Reddit’s ML-powered ad ranking systems through improved model architectures, contextual embeddings, and conversion-optimized modeling.
Requirements
- 7+ years of industry experience, including several years in applied ML roles
- Deep experience with DNN architectures and ML frameworks (TensorFlow, PyTorch)
- Strong background in recommendation systems, ads ranking, or similar domains
- Experience working with large-scale datasets and complex feature pipelines
- Strong problem-solving and experimentation skills
Responsibilities
- Design and train advanced ML models (e.g., DNNs, transformers) to power Reddit Ads Ranking
- Develop and optimize features including embeddings, contextual signals, and cross-session behavior
- Work closely with product, infra, and data teams to drive end-to-end model deployment and performance analysis
- Mentor other MLEs and contribute to modeling best practices across the org
- Shape the long-term modeling vision across one or more domains (conversion, app ads, shopping, brand, etc.)
Other
- Balancing generalization and specificity in modeling across different ad formats
- Managing trade-offs between model complexity, latency, and prediction quality
- Navigating cross-functional alignment to scale high-impact ML initiatives
- A dynamic, supportive work environment with a diverse team of engineers and cross-functional partners
- Opportunities for professional growth and development, with a focus on continuous learning and skill-building
