Staff ML Engineer, Ads Retrieval Leader

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

Benefits offered by this job

100% remote opportunity

Comprehensive Healthcare Benefits and

401k with Employer Match

Global Benefit programs

Family Planning Support

Gender-Affirming Care

Mental Health & Coaching Benefits

Flexible Vacation & Paid VolunteerTime

Generous Paid Parental Leave

Job summary

Reddit is hiring a Staff Machine Learning Engineer for the Ads Retrieval ML team to lead retrieval modeling and end-to-end product impact at scale. You will guide data design, model development, evaluation, and deployment while mentoring engineers and shaping long-term technical direction.

You will work with large-scale data, build advanced candidate-generation and retrieval systems, and collaborate with product and ads teams to improve advertiser outcomes and user experience.

Qualifications

• 7+ years of industry experience building and shipping applied ML products.
• Deep experience with information retrieval, candidate generation, recommender systems, or ranking.
• Strong understanding of retrieval modeling concepts, including DNNs, embeddings, two-tower/dual-encoder models, and ANN search.
• Experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.

Responsibilities

• Define the technical direction and multi-year roadmap for ads retrieval modeling.
• Design, develop, and launch candidate-generation and retrieval models for campaigns and ads.
• Apply modern approaches like two-tower architectures, embeddings, and sequence models to create product value.

Skills

Information retrieval

Recommender systems

Deep learning

TensorFlow

PyTorch

Production code

Experimentation

Communication

Tools

TensorFlow

PyTorch

NN search

Airflow

Job description

Reddit is hiring a Staff Machine Learning Engineer for the Ads Retrieval ML team to lead retrieval modeling and end-to-end product impact at scale. You will guide data design, model development, evaluation, and deployment while mentoring engineers and shaping long-term technical direction.

You will work with large-scale data, build advanced candidate-generation and retrieval systems, and collaborate with product and ads teams to improve advertiser outcomes and user experience.