Staff Machine Learning Engineer - LS Embedding

2 Months ago • 8 Years + • Research Development • $230,000 PA - $322,000 PA

Job Summary

Job Description

As a Staff Machine Learning Engineer, you will own the technical direction for large-scale embedding models, guiding the development of state-of-the-art graph-based ML architectures and high-impact representation learning strategies. You will partner with leadership to define ML roadmaps, drive innovation in large-scale graph embeddings and deep learning techniques, and ensure scalable, efficient deployment of ML models in production. This role offers an opportunity to influence key AI-driven systems across Reddit while mentoring and uplifting the team’s technical capabilities. Responsibilities include architecting next-generation multi-entity embeddings, leading research initiatives on scalable graph-based learning, and establishing real-time serving architectures.
Must have:
  • Experience in machine learning engineering with a focus on representation learning.
  • Expertise in Graph Neural Networks, graph-based representation learning, and transformers.
  • Understanding of graph theory, knowledge graphs, and complex multi-entity relationships.
  • Ability to design, implement, and optimize scalable ML architectures.
  • Hands-on experience with PyTorch Geometric, Deep Graph Library, TensorFlow, and JAX.
  • Strong software engineering skills in Python, C++, or similar languages.
  • Demonstrated leadership in driving ML strategy and mentoring engineers.
  • Experience with A/B testing and real-time feedback loops in production systems.
  • Excellent communication skills for presenting complex ML concepts.
Perks:
  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k Match
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Reddit Global Days off
  • Generous paid Parental Leave
  • Paid Volunteer time off

Job Details

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

About the Team

The LS Embedding Team is at the forefront of building highly expressive, multi-entity embeddings that power Reddit’s recommendation systems. We go beyond standard two-tower architectures, leveraging Graph Neural Networks (GNNs), large-scale transformer models, and cutting-edge representation learning techniques to enhance personalization across Reddit’s ecosystem. Our work impacts content discovery, user engagement, and platform growth at a massive scale.

About the Role

As a Staff Machine Learning Engineer, you will own the technical direction for large-scale embedding models, guiding the development of state-of-the-art graph-based ML architectures and high-impact representation learning strategies. You will partner with leadership to define ML roadmaps, drive innovation in large-scale graph embeddings and deep learning techniques, and ensure scalable, efficient deployment of ML models in production. This role offers an opportunity to influence key AI-driven systems across Reddit while mentoring and uplifting the team’s technical capabilities.

Responsibilities

  • Architect and lead the development of next-generation multi-entity embeddings, leveraging Graph Neural Networks (GNNs), transformers, and large-scale representation learning techniques.
  • Define and execute the ML strategy for embedding models, identifying opportunities to enhance personalization and recommendation quality across Reddit.
  • Lead research initiatives on scalable graph-based learning, self-supervised techniques, and real-time adaptation, bringing cutting-edge advancements into production.
  • Partner with ML infrastructure teams to build high-performance, distributed training systems that efficiently 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 cross-functionally with teams in Feed Ranking, Ads, Content Understanding, and Core ML to integrate embeddings into Reddit’s key AI-driven systems.
  • Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing.
  • Stay at the forefront of AI research, evaluating and introducing new modeling paradigms to keep Reddit’s ML ecosystem at the cutting edge.
  • Drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making.

Qualifications

  • 8+ years of experience in machine learning engineering, with a strong focus on representation learning, large-scale embeddings, and recommendation systems.
  • Expertise in Graph Neural Networks (GNNs), graph-based representation learning, and transformer architectures.
  • Deep understanding of graph theory, knowledge graphs, and complex multi-entity relationships in machine learning applications.
  • Proven ability to design, implement, and optimize scalable ML architectures, from distributed training to real-time inference.
  • Hands-on experience with PyTorch Geometric (PyG), Deep Graph Library (DGL), TensorFlow, JAX, and large-scale ML model optimization.
  • Strong software engineering skills in Python, C++, or similar languages, with experience in 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, with the ability to effectively present complex ML concepts to technical and non-technical stakeholders.

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k Match
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Reddit Global Days off
  • Generous paid Parental Leave  
  • Paid Volunteer time off

 

 

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