Staff Machine Learning Engineer, Ads Foundational Representations

Details

Reddit's Ads Foundational Representations team develops signals and representations of core entities such as ads, posts, and users. The team builds embeddings that capture semantic, contextual, and behavioral information to improve Reddit Ads, including targeting, auctions, Business Insights, and advertiser-facing products such as creative generation and optimization.

The team focuses on multimodal and content embeddings, contextual and behavioral relevance, knowledge graph embeddings, user intent modeling, and LLM-based representations using LLMs, VLMs, and foundational models.

As a Staff Machine Learning Engineer, you will set the technical direction for multiple team pillars and lead cross-functional machine learning projects from business gap analysis through engineering execution. Approximately 50% of the role involves technical leadership and mentorship, with the remaining 50% focused on hands-on data analysis, engineering, modeling, and automation.

Responsibilities

• Provide technical leadership and mentorship to machine learning engineers by driving designs and reviews, establishing best practices in analysis, modeling, and engineering, and maintaining a high quality bar.
• Work with team and organizational leadership to develop technical strategy for content-based embeddings and advertising relevance.
• Develop and iterate on embedding models for advertising use cases, including aggregation pipelines, two-tower architectures, and sequence models.
• Work with local and third-party LLMs and VLMs to extract representations, develop evaluation methodologies, prompt-tune and fine-tune large models, and build state-of-the-art embeddings.
• Build data processing and inference pipelines for machine learning models.
• Perform qualitative and quantitative evaluation, including internal benchmarking, downstream recommender-system offline metrics, and online experiments.
• Ensure the reliability, scalability, and performance of machine learning systems through automated testing, performance monitoring, and model-management best practices.
• Participate in modeling and coding reviews and provide feedback on quality and performance.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

Requirements

• 7+ years of hands-on experience designing, training, evaluating, testing, and deploying industry-level models across the full lifecycle.
• Staff-level technical leadership experience, including mentoring engineers, establishing standards, raising the quality bar, and leading complex cross-functional projects from requirements and design through alignment and execution without direct people-management authority.
• Excellent verbal and written communication skills, including the ability to explain complex technical concepts to different audiences.
• Strong experience with content-rich NLP or computer vision problems at scale and using embeddings to solve them.
• A data-driven approach to machine learning system development and willingness to investigate the underlying data behind metrics.
• Familiarity with the advertising domain and/or search or recommender systems.
• Experience with mainstream deep learning frameworks such as PyTorch or TensorFlow.

Preferred Qualifications

• Experience with Python, PyTorch, Airflow, BigQuery, Ray, Kubernetes, Kafka, and GCP.
• Experience mentoring junior engineers and leading complex projects.
• Hands-on experience using, fine-tuning, or building large language models.

Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Global benefits covering workspace, professional development, caregiving support, and other needs.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Generous paid parental leave.

Compensation

The base salary range is $230,000–$322,000 USD per year. The position is also eligible for equity in the form of restricted stock units and, depending on the position offered, may be eligible to receive a commission. Final offer amounts depend on factors including skills, depth of experience, and relevant licenses or credentials.

Reddit has a flexible-first workforce. The role is based in New York City, and employees may work remotely from anywhere on the U.S. East Coast in Eastern Time.