The LS Embedding team will focus on building highly expressive multi-entity large scale embeddings exploring architectures beyond standard two-tower approaches to enhance our recommendation systems at Reddit. This entails modelling various compound interactions and relationships between users and entities they interact with using Graphs and exploring Graph neural networks and transformers to encode them.
We are looking for a Principal Machine Learning Engineer to lead the design and architecture of GNN and transformers based multi-entity embedding generation actively participating in end-to-end implementation process including enabling efficient distributed training and serving for such architectures shaping the future of recommendation systems at Reddit.
If applying ML / AI in production to improve Reddit Relevance excites you, then you’ve found the right place.
RESPONSIBILITIES:
Lead the team that architects and designs GNN and transformers based multi-entity embedding generation.
- Define the technical roadmap and plan of execution in collaboration with Xfn partners.
- Develop and optimize large-scale graph-based machine learning pipelines for recommendation systems.
- Architect scalable and efficient GNN and transformers-based recommendation models that can process complex, interconnected data structures.
- Collaborate with cross functional business units such as Ads teams leveraging the models for upstream functions and improve relevance metrics.
- Collaborate with ML Infrastructure teams to enable distributed GPU based training and online serving architecture
- Lead feature engineering efforts to identify and curate expressive raw data to be used for creating embeddings
- Be a mentor and cross-functional advocate for the team
- Contribute towards team and product strategy, operations and execution at Reddit.
QUALIFICATIONS:
- 15+ years of Technical Leadership Experience
- Proven ability to lead ML initiatives, mentor engineers, and communicate complex concepts to cross-functional teams.
- Expertise in Graph Neural Networks, collaborative filtering, knowledge graphs, and deep learning for recommendations.
- Understanding of graph theory, network science, and representation learning technique
- Strong coding skills in Python and experience with ML frameworks like PyTorch Geometric (PyG), Deep Graph Library (DGL), TensorFlow, and scikit-learn.
- Solid understanding of ML infrastructure components and libraries (data parallel, model parallel, pipeline parallel, torch.inductor, model pruning, etc.) enabling efficient distributed training and inference.
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
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Top Skills
Reddit Santa Monica, California, USA Office
2403 Main Street, Santa Monica, California, United States, 90405
Similar Jobs
What you need to know about the Los Angeles Tech Scene
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
