Reddit, Inc.Remote
Staff Machine Learning Engineer, Ads Measurement Modeling
United States of America
Full Time
6 days ago
$230,000 - $322,000 USD
H1B Sponsor Likely
Key skills
Machine learningAds measurement modelingIdentity resolutionTensorFlowPyTorchFeature engineeringModel trainingModel inferenceLarge-scale data processingDistributed computingSparkKafkaBeamFlinkMachine LearningMLLeadershipMentoringProduct ManagementCommunicationCollaboration
About this role
Reddit is a community of communities, dedicated to enhancing the efficiency of its advertising platform through innovative solutions. The Staff Machine Learning Engineer will lead the technical strategy and architecture for ads identity modeling solutions, overseeing end-to-end ML workflows and collaborating with cross-functional teams.
Responsibilities:
- Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models
- Design and train advanced ML models while ensuring accuracy, scalability, and compliance with privacy requirements, managing trade-offs between complexity, latency, and prediction quality
- 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
Requirements:
- 7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale
- Demonstrated experience architecting and building ads measurement modeling solutions leveraging advanced machine learning 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