Staff ML Engineer - Ads Retrieval & Targeting (Remote)

Fdetimes; United States; Remote; USD 230,000 - 322,000; Full time

Benefits offered by this job

100% remote opportunity

401k with Employer Match

Healthcare Benefits

Mental Health & Coaching Benefits

Flexible Vacation & Paid Volunteer

Generous Paid Parental Leave

Job summary

Reddit is seeking a Staff Machine Learning Engineer to lead the Retrieval and Targeting ML team. This role guides retrieval model design, experimentation, and end-to-end product impact at Reddit scale, staying close to data, objectives, and production deployment.

You will mentor engineers, shape multi-year directions, and collaborate with ads, ranking, and product teams to ensure retrieval models align with business and user outcomes.

Qualifications

• 7+ years of industry experience, including substantial experience building and shipping applied ML products.
• Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
• Strong understanding of retrieval modeling concepts, including DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
• Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
• Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
• Strong command of experimental design and model evaluation, including how offline retrieval metrics relate to downstream business and user metrics.
• Experience working with large-scale behavioral, contextual, or content datasets and complex feature pipelines.
• Strong software engineering fundamentals and the ability to write clear, reliable, maintainable production code.
• Technical leadership experience: setting direction, leading complex projects, influencing partner teams, and mentoring other engineers.
• Excellent written and verbal communication, with the ability to explain complex modeling choices to technical and non-technical audiences.

Responsibilities

• Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders.
• Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit’s advertising surfaces.
• Apply modern approaches such as two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and other deep learning techniques when they create meaningful product value.
• Improve the retrieval stack across key modeling decisions, including objectives, labels, sampling strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.
• Work with approximate nearest-neighbor and vector retrieval systems, reasoning about recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.
• Establish strong evaluation practices that connect retrieval metrics—such as recall, precision, candidate coverage, calibration, and downstream lift—to ads and user outcomes.
• Lead offline analysis and online experiments, interpret ambiguous results, and translate findings into the next modeling iteration.
• Partner with downstream ranking, ads platform, auction, measurement, and product teams to ensure retrieval models integrate effectively into the full ads funnel.
• Write design documents, review code and model changes, and raise the quality bar for modeling, testing, observability, and production ownership.
• Mentor ML engineers and help grow the team’s expertise in retrieval, recommendation, and representation learning.

Skills

Information retrieval

Recommender systems

Model evaluation

Leadership

Communication

Tools

TensorFlow

PyTorch

Job description

Reddit is seeking a Staff Machine Learning Engineer to lead the Retrieval and Targeting ML team. This role guides retrieval model design, experimentation, and end-to-end product impact at Reddit scale, staying close to data, objectives, and production deployment.

You will mentor engineers, shape multi-year directions, and collaborate with ads, ranking, and product teams to ensure retrieval models align with business and user outcomes.