Senior Engineering Manager, Unified Embeddings Platform

Reddit Reddit · Consumer · United States · Remote · Machine Learning

Senior Engineering Manager to lead the Unified Embeddings Platform team at Reddit. This role will architect, implement, and maintain a platform for foundational ML embeddings using state-of-the-art architectures like GNNs, foundational models, and sequence models. The platform will empower ML engineers and data scientists across Reddit to improve the ML feature software development lifecycle, enabling access, storage, and sharing of embeddings.

What you'd actually do

  1. Lead the creation of foundational embeddings at Reddit leveraging state of the art architectures such as graph neural networks, transformer based sequence models, foundational models, etc.
  2. Lead the design and long-term evolution of Reddit’s Embeddings platform enabling all ML teams access, store and share embeddings
  3. Drive high-impact, high-leverage projects that align with Reddit’s broader engineering and business goals
  4. Build and grow a high-performing team, including hiring, mentoring, and creating a culture of technical excellence
  5. Establish and champion best practices for the production, consumption, and governance of machine learning features

Skills

Required

  • People management
  • Production software development
  • Scalability
  • Reliability
  • Performance
  • Ease of use
  • Large-scale ML Systems
  • Self-service platform development
  • ML feature development lifecycle
  • Graph Neural Networks
  • Transformer based sequence models
  • Foundational models

Nice to have

  • Mentoring
  • Hiring
  • Technical excellence
  • Best practices for ML feature production, consumption, and governance
  • Thought partnership with product and upper management
  • Communication with cross-functional stakeholders

What the JD emphasized

  • 4+ years of experience in people management
  • 8+ years of work experience in a production software development environment
  • Strong focus on scalability, reliability, performance, and ease of use.
  • Experience working on large-scale ML Systems serving 100s of millions of users
  • Experience building self service platform enabling storage and sharing of large scale data and embeddings
  • Experience with leading modelling teams powering the creation of foundational embeddings based on state of the art architectures

Other signals

  • ML Platform
  • Embeddings
  • Graph Neural Networks
  • Foundational Models
  • Transformer Models
  • ML Feature Development Lifecycle