Staff Machine Learning Engineer - Ads Retrieval

Reddit is home to over 100,000 active communities and approximately 130 million daily active unique visitors. Sitting at the heart of the ads delivery funnel, the Ads Retrieval ML team builds the machine learning platforms that identify candidate advertising campaigns before downstream ranking and auction decisions occur.

As a Staff Machine Learning Engineer, you will provide overall technical leadership for the Retrieval and Targeting ML organization. You will define the multi-year roadmap and design candidate generation models that optimize relevance, advertiser outcomes, and user experience at Reddit scale. In this hands-on technical leadership role, you will lead the end-to-end lifecycle—from objective formulation, negative sampling, and representation learning through deep learning model development (two-tower architectures, sequence models, vector search), offline evaluation, online A/B testing, and production deployment.

Key Responsibilities

• Technical Direction & Strategic Roadmap: Define the technical vision and long-term roadmap for ads retrieval modeling in partnership with Engineering, Product, Data Science, and Ads Platform teams.
• Candidate Generation & Deep Learning: Design and launch scalable candidate generation models using two-tower (dual-encoder) architectures, representation learning, sequence models, and graph-based embeddings.
• Retrieval Stack Optimization: Optimize key modeling decisions, including loss objectives, negative sampling strategies, hard-negative mining, feature pipelines, embedding generation, and candidate filtering depth.
• Vector Search & ANN Engineering: Work with Approximate Nearest Neighbor (ANN) and vector retrieval systems, balancing recall, precision, latency, freshness, coverage, and infrastructure cost trade-offs.
• Evaluation & A/B Experimentation: Establish rigorous offline and online evaluation frameworks connecting retrieval metrics (recall@K, coverage, calibration) directly to downstream ad auction and user outcomes.
• Cross-Funnel Integration: Collaborate with downstream ranking, ad serving, auction, and measurement engineering teams to ensure seamless multi-stage funnel integration.
• Mentorship & Technical Governance: Conduct design reviews, write technical specs, raise modeling and observability standards, and mentor ML engineers across the organization.

Requirements

Experience & Applied ML Background

• 7+ years of industry experience building, scaling, and shipping applied machine learning products.
• Deep expertise in information retrieval, candidate generation, recommender systems, or ranking platforms.
• Hands-on mastery of retrieval concepts, including deep neural networks (DNNs), embeddings, two-tower/dual-encoder models, approximate nearest-neighbor (ANN) search, and multi-stage retrieval pipelines.
• Extensive experience training, debugging, and deploying deep learning models using PyTorch, TensorFlow, or similar ML frameworks.

Systems & Experimental Design

• Strong command of experimental design, offline-to-online evaluation alignment, and A/B testing.
• Experience operating with large-scale behavioral, contextual, or content datasets and feature pipelines.
• Solid software engineering fundamentals with the ability to write clean, maintainable production code.
• Demonstrated technical leadership: setting direction, leading multi-team projects, and mentoring senior engineers.

Preferred Qualifications

• Direct domain experience in ads retrieval, ads ranking, ad targeting, or marketplace optimization.
• Experience modeling interaction signals using sequential architectures (Transformers, RNNs), graph neural networks, or multimodal signals.
• Track record of shipping ML models within ads marketplaces at peer tech companies.
• Publications, patents, or open-source industry contributions in applied ML or ranking systems.

Total Rewards & Benefits

• 100% Remote Flexibility: Work remotely anywhere in the US, or utilize office hubs in New York, San Francisco, Los Angeles, or Chicago.
• Compensation & Equity: Base salary range of $230,000 – $322,000 USD + Restricted Stock Units (RSUs) + 401(k) program with employer match.
• Health & Family Care: 100% comprehensive healthcare coverage, gender-affirming care, mental health coaching, family planning support, and generous paid parental leave.
• Time Off & Stipends: Flexible vacation policy, paid volunteer time off, workspace stipends, and dedicated professional development allowances.