Senior Machine Learning Engineer

About The Position

Reddit is a community of communities, built on shared interests, passion, and trust. Machine learning is central to how millions of people discover, connect, and engage with conversations on Reddit. ML engineers tackle interesting and impactful problems in large-scale applied machine learning, working on a wide range of high-impact problems across the Consumer and Ads organizations. This role is for individuals excited to build systems end-to-end, from research and modeling to production deployment, and who want to shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you.

Requirements

3-5+ years of experience building, deploying, and operating machine learning systems in production.
Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals.
A strong grasp of ML algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs).
Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow).
Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure.
Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions.
Experience improving measurable metrics through applied machine learning.

Nice To Haves

Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems.
Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.).
Experience working with real-time systems and low-latency production environments.
Background in feature engineering, model optimization, and production monitoring.
Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale.
Advanced degree in Computer Science, Machine Learning, or related quantitative field.

Responsibilities

Design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems; intelligent advertising systems; content, advertiser, and user understanding; large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems; and applied AI and LLM-driven experiences.
Operate on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.
Design, build, and deploy production-grade machine learning models and systems at scale.
Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring.
Build scalable data and model pipelines with strong reliability, observability, and automated retraining.
Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.
Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions.
Improve system performance across latency, throughput, and model quality metrics.
Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment.
Contribute to technical strategy, architecture, and long-term ML roadmap.

Benefits

Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
Equity in the form of restricted stock units
Potential for commission
Medical, dental, and vision insurance
Generous time off for vacation
Parental leave