Staff Machine Learning Infrastructure Engineer, Embedding Platform

Responsibilities

• Architect and lead the development of next-generation, large-scale machine learning techniques.
• Define and execute ML strategy to improve personalization and recommendation quality.
• Lead research initiatives on scalable machine learning systems and real-time model adaptation, bringing advancements into production.
• Partner with ML infrastructure teams to build high-performance, distributed training systems that scale across multiple GPUs and cloud environments.
• Establish and optimize real-time serving architectures for large-scale embeddings, ensuring low-latency inference and high throughput.
• Collaborate with Feed Ranking, Ads, Content Understanding, and Core ML teams to integrate models into AI-driven systems.
• Mentor and guide ML engineers while fostering technical excellence, innovation, and knowledge sharing.
• Evaluate and introduce new modeling paradigms and contribute to long-term ML planning.
• Drive technical discussions and present findings to leadership and stakeholders.

Requirements

• 8+ years of experience in machine learning engineering, focused on large-scale ML systems and recommendation or personalization systems.
• Expertise in modern deep learning architectures, including sequence models and foundational models.
• Deep understanding of complex multi-entity relationships and their modeling in large-scale systems.
• Experience designing, implementing, and optimizing scalable ML architectures, distributed training, and real-time inference.
• Strong software engineering skills in Python, C++, or similar languages.
• Experience with ML infrastructure, high-performance computing, and cloud-based ML pipelines.
• Demonstrated leadership in driving ML strategy, mentoring engineers, and influencing cross-functional teams.
• Experience with A/B testing, model evaluation frameworks, and real-time feedback loops in large-scale production systems.
• Excellent communication skills for presenting complex ML concepts to technical and non-technical stakeholders.

Compensation and Benefits

• Base salary: $253,300–$354,600 USD
• Equity in the form of restricted stock units; select positions may also be eligible for commission.
• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Global benefits supporting workspace, professional development, and caregiving.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Paid parental leave.