Reddit, Inc.Remote
Staff Machine Learning Engineer, Ads Measurement Modeling
United States of America
Full Time
1 hour ago
$230,000 - $322,000 USD
H1B Sponsor Likely
Key skills
Machine LearningAds Measurement ModelingIdentity ResolutionTensorFlowPyTorchFeature EngineeringModel TrainingModel InferenceLarge-scale Data ProcessingDistributed ComputingSparkKafkaBeamFlinkMLLeadershipMentoringProduct ManagementCommunicationCollaboration
About this role
Reddit is a community-driven platform dedicated to open and authentic conversations. They are seeking a Staff Machine Learning Engineer to lead the technical strategy for ads identity modeling solutions, ensuring the implementation of advanced ML models and best engineering practices.
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