Senior Machine Learning Engineer, LS Embedding Remote - United States

Remote Full-time
About

Senior Machine Learning Engineer, LS Embedding

Remote - United States 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 focuses on developing highly expressive, multi-entity embeddings to enhance Reddit’s recommendation systems. We go beyond standard two-tower architectures, leveraging graph-based modeling, Graph Neural Networks (GNNs), and transformer-based architectures to capture complex interactions between users and entities. Our work directly impacts personalization and relevance across Reddit’s platform. About the Role

We are seeking a Senior Machine Learning Engineer to design, develop, and optimize graph-based ML models for large-scale recommendation systems. You will work on embedding generation, distributed training, and scalable serving architectures, playing a key role in improving Reddit’s AI-powered personalization. This role offers the opportunity to contribute to cutting-edge ML research and apply it at scale in a high-impact production environment. Responsibilities

Design and implement scalable, high-performance machine learning models using Graph Neural Networks (GNNs), transformers, and knowledge graph approaches. Develop and optimize large-scale embedding generation pipelines for Reddit’s recommendation systems. Collaborate with ML infrastructure teams to enable efficient distributed training (multi-GPU, model/data parallelism) and low-latency serving. Work closely with cross-functional teams (Ads, Feed Ranking, Content Understanding) to integrate embeddings into various personalization and ranking systems. Drive feature engineering efforts, identifying and curating expressive raw data to enhance model effectiveness. Monitor, evaluate, and improve model performance using A/B testing, offline metrics, and real-time feedback loops. Stay up-to-date with the latest research in GNNs, transformers, and representation learning, bringing new ideas into production. Participate in code reviews, mentor junior engineers, and contribute to technical decision-making. Qualifications

5+ years of experience in machine learning engineering, with a strong focus on recommendation systems, representation learning, and deep learning. Hands-on experience with Graph Neural Networks (GNNs), collaborative filtering, and large-scale embeddings. Proficiency in Python and experience with ML frameworks such as PyTorch Geometric (PyG), Deep Graph Library (DGL), TensorFlow, or JAX. Strong understanding of graph theory, network science, and representation learning techniques. Experience building distributed training and inference systems using ML infrastructure components (data parallelism, model pruning, inference optimization, etc.). Ability to work in a fast-paced environment, balancing innovation with high-quality production deployment. Strong communication skills and the ability to collaborate cross-functionally with engineers, researchers, and product teams. Compensation and Benefits

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

redditinc.com/careers . The base pay range for this position is: $216,700 - $303,400 USD Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.• indicates a required field

#J-18808-Ljbffr

Nice-to-have skills
• Python
• TensorFlow
• California, United States

Work experience
• Machine Learning

Languages
• English

Apply Now

Apply Now

Similar Opportunities

Experienced Registered Behavior Technician for In-Home ABA Therapy - Atlanta, GA

Remote Full-time

Immediate Hiring: Experienced Registered Behavioral Technician (RBT) for Clinic-Based ABA Therapy Services

Remote Full-time

Experienced Registered Behavioral Technician (RBT) - ABA Therapy for Children with Autism Spectrum Disorder

Remote Full-time

Experienced Registered Nurse - Telehealth: Providing Remote Care Coordination and Patient Support

Remote Full-time

Experienced Substitute Teacher for Riverside County Schools - Join Scoot Education's Innovative Team

Remote Full-time

Experienced Substitute Teacher for San Bernardino County - Flexible Schedules & Competitive Pay

Remote Full-time

Experienced School Year Instructional Coach for High-Dosage Tutoring Programs in Edgewater Park, NJ

Remote Full-time

Experienced School Year Tutor for K-8 Students in Math and Literacy - Mickleton, NJ

Remote Full-time

Experienced Secondary Social Studies Teacher for Kansas - Flexible Hybrid Remote Arrangement

Remote Full-time

USPS Office Helper

Remote Full-time

Summer Internship: Science Communication Intern

Remote Full-time

Teacher - 8th Grade Science (McDonald) in McDonald, TN

Remote Full-time

Breaking News Reporter, Weekend

Remote Full-time

Lead Generation Call Center Specialist I (Remote)

Remote Full-time

Senior Consultant – Cyber Risk Advisory | Remote US

Remote Full-time

Staff Data Analyst - Clinical & Population Health

Remote Full-time

[Remote] Service Representative

Remote Full-time

Virtual Administrative Support Roles - Flexible Remote Opportunities

Remote Full-time

Mulesoft Developer

Remote Full-time

Part-Time Remote Amazon Product Data Entry Specialist – E-Commerce Listing & Information Management (Flexible 4-Hour Daily Schedule)

Remote Full-time
← Back to Home