Staff Machine Learning Infrastructure Engineer, Embedding Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and spearhead the development of next-generation, large-scale machine learning techniques.

• Formulate and implement the ML strategy, pinpointing opportunities to improve personalization and recommendation quality throughout Reddit.

• Lead research projects on scalable machine learning systems and real-time model adaptation, integrating state-of-the-art advancements into production.

• Collaborate with ML infrastructure teams to create high-performance, distributed training systems that efficiently scale across various GPUs and cloud environments.

• Set up and optimize real-time serving architectures for large-scale embeddings, ensuring low-latency inference and high throughput.

• Work cross-functionally with teams in Feed Ranking, Ads, Content Understanding, and Core ML to incorporate ML models into Reddit’s essential AI-driven systems.

• Mentor and support senior and mid-level ML engineers, nurturing a culture of excellence, innovation, and knowledge sharing.

• Remain at the cutting edge of AI research, assessing and introducing new modeling paradigms.

• Facilitate technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making.

⛳️ Requirements

• Over 8 years of experience in machine learning engineering, concentrating on large-scale ML systems and recommendation or personalization systems.

• Proficiency in modern deep learning architectures, including sequence models and foundational models.

• In-depth understanding of intricate multi-entity relationships in ML applications and large-scale system modeling.

• Proven capability to design, implement, and optimize scalable ML architectures, ranging from distributed training to real-time inference.

• Strong software engineering skills in Python, C++, or similar programming languages.

• Experience in ML infrastructure, high-performance computing, and cloud-based ML pipelines.

• Demonstrated leadership in formulating ML strategy, mentoring engineers, and influencing cross-functional teams.

• Familiarity with A/B testing, model evaluation frameworks, and real-time feedback loops in large-scale production systems.

• Excellent communication skills for articulating complex ML concepts to both technical and non-technical stakeholders.

🏝️ Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs.

• 401k with Employer Match.

• Global Benefit programs that fit your lifestyle, including workspace, professional development, and caregiving support.

• Family Planning Support.

• Gender-Affirming Care.

• Mental Health & Coaching Benefits.

• Flexible Vacation & Paid Volunteer Time Off.

• Generous Paid Parental Leave.

• Equity in the form of restricted stock units.

• Medical, dental, and vision insurance.

• 401(k) program with employer match.

• Generous time off for vacation.

• Parental leave.

• Opportunity to opt out of interview recording, transcription, and summarization.