Staff Machine Learning Engineer, Ads Measurement Modeling

Minimum Qualifications

• 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

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