Principal Machine Learning Engineer

Summary

Join Reddit's Ads Measurement Org as a Principal Machine Learning Engineer and lead end-to-end Ads initiatives. You will leverage your expertise in identity resolution and graph-based systems to drive architectural decisions, mentor peers, and tackle technical challenges. Responsibilities include leading the technical strategy for the identity resolution system, developing ML models for probabilistic user matching, overseeing end-to-end ML workflows, and partnering with cross-functional teams. You will establish engineering best practices and mentor junior engineers. This role requires 10+ years of software engineering experience, including 5+ years focused on ML-driven systems at scale, and expertise in identity graphs and probabilistic techniques. Strong knowledge of various identifiers and proficiency in machine learning frameworks are essential.

Requirements

• 10+ years of professional software engineering experience, with at least 5+ years focused on ML-driven systems at scale
• Demonstrated experience architecting and building identity graphs, device graphs, or similar identity matching solutions leveraging probabilistic techniques
• Strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference
• Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink)
• Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal)
• Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for identity resolution

Responsibilities

• Lead the technical strategy and architecture for our company’s identity resolution system, ensuring accuracy, scalability, and compliance with privacy requirements
• Develop and refine ML models for probabilistic user matching using multiple identifiers (cookies, IP addresses, hashed emails, phone numbers, user agents)
• Oversee end-to-end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment—optimizing for performance and cost
• Partner with cross-functional teams (e.g., product management, data science, platform engineering, privacy, legal) to define the roadmap and set long-term goals
• Establish engineering best practices, code quality standards, and data governance guidelines to ensure maintainability and trustworthiness of the identity graph
• Mentor and coach junior engineers, fostering a culture of innovation, technical excellence, and knowledge sharing across the organization

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k Match
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Reddit Global Days off
• Generous paid Parental Leave
• Paid Volunteer time off