Principal Engineer, ML

Responsibilities

• Define and drive the long-term technical vision, architecture, and strategy for the Ads Serving & ML Platform.
• Lead the design and evolution of large-scale advertising systems covering retrieval, ranking, auction, targeting, pacing, and measurement.
• Drive modernization involving large language models, generative AI, real-time inference, and next-generation ML infrastructure.
• Lead strategic technical investments that improve advertiser outcomes, customer experience, scalability, operational efficiency, and revenue.
• Partner with engineering, machine learning, product, and business leaders to align technical direction with company priorities.
• Influence architecture and engineering practices across multiple organizations through technical leadership, design reviews, and mentorship.
• Establish best practices for reliability, performance, scalability, observability, and operational excellence.
• Drive measurable improvements in engagement, conversion, relevance, advertiser ROI, revenue growth, system efficiency, and cost.
• Serve as a recognized technical leader and domain expert in large-scale advertising systems and machine learning platforms.

Requirements

• 12+ years of experience building large-scale software platforms, machine learning systems, or distributed infrastructure.
• Proven experience architecting and operating mission-critical, high-throughput online systems at internet scale.
• Deep expertise in at least one user-facing ML domain such as advertising, search, recommendations, or personalization.
• Strong understanding of model training, feature engineering, experimentation, online inference, evaluation, and production operations.
• Experience building and scaling AI/ML serving infrastructure, including GPU- and CPU-based optimization for latency, throughput, and cost.
• Strong understanding of LLMs, foundation models, RAG, and production AI serving architectures.
• Deep knowledge of retrieval and ranking systems, relevance, personalization, candidate generation, ranking, experimentation, and model evaluation.
• Demonstrated ability to create significant business impact through technical innovation and platform evolution.
• Ability to influence technical direction across multiple teams and organizations without direct authority.
• Strong software engineering skills in Java, C++, or Python.
• Experience developing distributed systems that process and serve large-scale datasets with high availability and low latency.
• MS or higher in Computer Science, Engineering, or a related technical discipline.
• Preferred: experience with large-scale advertising, ad ranking, auction, sponsored search, e-commerce, marketplaces, consumer internet, real-time ML, recommendation systems, search infrastructure, personalization platforms, architectural transformation, or high-growth technology companies.
• Preferred: PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

Benefits

• Medical, dental, vision, life, and AD&D insurance.
• Flexible Spending Accounts and Health Savings Account.
• Long-term and short-term disability coverage and Employee Assistance Program.
• 401K plan with company match.
• 18–21 days of paid time off per year based on tenure.
• 12 public holidays and paid parental leave.
• Pre-tax commuter benefits.
• Free electric car charging station.
• Base pay ranges from $207,900 to $386,100 per year across US geographic markets; additional compensation may include bonuses or equity.