Staff Machine Learning Engineer (Ads Modeling)

Location: Remote - United States; 100% remote opportunity. Hybrid and onsite work is also available at offices in New York, San Francisco, Los Angeles, and Chicago.

Base salary: $230,000–$322,000 USD per year, plus potential equity and commission depending on the position offered.

Company

Reddit operates a large community platform and develops ML-powered advertising and ranking systems.

What you will do

• Design and train advanced machine learning models, including deep neural networks and transformers, for Reddit Ads Ranking.
• Develop and optimize embeddings, contextual signals, and cross-session behavior features.
• Collaborate with product, infrastructure, and data teams on model deployment, feature serving, and performance analysis.
• Mentor machine learning engineers and contribute to modeling best practices across the organization.
• Shape the long-term modeling vision for conversion, app ads, shopping, brand, and related domains.

Requirements

• 7+ years of industry experience, including several years in applied machine learning.
• Strong experience with deep learning architectures and TensorFlow or PyTorch.
• Strong background in recommendation systems, ads ranking, or similar performance-driven domains.
• Experience with large-scale datasets, complex feature pipelines, and production model deployment.
• Knowledge of recommendation systems or the ads funnel, including state-of-the-art ads or recommender models.
• Strong problem-solving, experimentation, and cross-functional collaboration skills.

Nice to have

• Experience with conversion modeling, app ads, performance ads, or brand ads.
• Experience in ads marketplaces at peer companies.
• Publications, patents, or industry contributions in applied machine learning or ranking systems.

Culture & Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Workspace, professional development, caregiving, family planning, gender-affirming care, and mental health benefits.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.
• Flexible remote, hybrid, and onsite work options.

Hiring process

• Some interviews may be recorded, transcribed, and summarized by AI, with an option to opt out before the interview.
• Interview recordings are deleted promptly after a hiring decision.