Senior Engineering Manager, Unified Embeddings Platform

What You'll Do: As a Senior Engineering Manager, Unified Embeddings Platform, you will work lead our Embeddings Platform Team and be instrumental in architecting, implementing, and maintaining platform providing foundational ML embeddings based on state of the art architectures such as large scale graph neural networks, foundational models, large scale sequence models, etc. empowering all product verticals at Reddit to fulfill Reddit's mission of bringing community and belonging to everyone in the world.

You'll partner with teams across Reddit infrastructure and ML modelling at the center of machine learning to enable machine learning engineers (MLEs) and data scientists (DSs) to improve the ML feature software development lifecycle.

- 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.

- Lead the design and long-term evolution of Reddit's Embeddings platform enabling all ML teams access, store and share embeddings

- Drive high-impact, high-leverage projects that align with Reddit's broader engineering and business goals

- Build and grow a high-performing team, including hiring, mentoring, and creating a culture of technical excellence

- Establish and champion best practices for the production, consumption, and governance of machine learning features

- Serve as a thought partner to product and upper management to ensure your team's plans align with company goals.

- Communicate your team's work and set expectations with cross-functional stakeholders.

- 8+ years of work experience in a production software development environment

- Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle.

- 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