Reddit

Senior Machine Learning Engineer

Reddit$130K — $180K *
US-AnywhereRemote in Ontario, CA
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of hands-on experience with ML model training and production deployment.
  • Proficient in programming languages like Python or Scala with software development best practices.
  • Experience with major ML frameworks such as TensorFlow or PyTorch.
  • Ability to collaborate with cross-functional teams to develop technical solutions based on business needs.
  • Demonstrated success in utilizing ML to achieve performance improvements.

Responsibilities

  • Design and deploy machine learning models for ad ranking and optimization.
  • Manage the entire ML lifecycle from ideation to deployment.
  • Conduct feature engineering to enhance model performance.
  • Collaborate with product and engineering teams to create effective ML solutions.
  • Enhance the reliability of ML systems with monitoring and retraining processes.
  • Stay updated on ML advancements to inform team strategies.

Benefits

  • Flexible work environment with options for remote or in-office work.
  • Opportunity to work on impactful, large-scale systems in the advertising domain.
  • Access to cutting-edge ML techniques and tools.
  • Engagement with cross-functional teams, enhancing collaboration and skills.
  • Commitment to diversity and inclusion within the workplace.
Full Job Description
What You'll Work On

As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:
  • Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
  • Intelligent advertising systems including ranking, bidding, measurement, and optimization
  • Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
  • Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
  • Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement

You'll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.

What You'll Do
  • 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

Basic Qualifications
  • 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
  • ML Fundamentals: a strong grasp of 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

Preferred Qualifications
  • 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

Potential Teams
  • Ads Measurement Modeling
  • Ads Targeting and Retrieval
  • Advertiser Optimization
  • Ads Marketplace Quality
  • Ads Creative Effectiveness
  • Ads Foundational Representations
  • Ads Content Understanding
  • Ads Ranking
  • Feed Relevance
  • Search and Answers Relevance
  • ML Understanding
  • Notifications Relevance

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

About Reddit

Reddit is an American social news aggregation, web content rating, and discussion website. Registered members submit content to the site such as links, text posts, images, and videos, which are then voted up or down by other members. Posts are organized by subject into user-created boards called "communities" or "subreddits", which cover topics such as news, politics, religion, science, movies, video games, music, books, sports, fitness, cooking, pets, and image-sharing. Submissions with more upvotes appear towards the top of their subreddit and, if they receive enough upvotes, ultimately on the site's front page. Although there are strict rules prohibiting harassment, it still occurs, and Reddit administrators moderate the communities and close or restrict them on occasion. Moderation is also conducted by community-specific moderators, who are not considered Reddit employees. As of September 2021, Reddit ranks as the 19th-most-visited website in the world and 7th most-visited website in the U.S., according to Alexa Internet. About 42–49.3% of its user base comes from the United States, followed by the United Kingdom at 7.9–8.2% and Canada at 5.2–7.8%. Twenty-two percent of U.S. adults aged 18 to 29 years, and 14 percent of U.S. adults aged 30 to 49 years, regularly use Reddit. Reddit was founded by University of Virginia roommates Steve Huffman and Alexis Ohanian, with Aaron Swartz, in 2005. Condé Nast Publications acquired the site in October 2006. In 2011, Reddit became an independent subsidiary of Condé Nast's parent company, Advance Publications. In October 2014, Reddit raised $50 million in a funding round led by Sam Altman and including investors Marc Andreessen, Peter Thiel, Ron Conway, Snoop Dogg, and Jared Leto. Their investment valued the company at $500 million then. In July 2017, Reddit raised $200 million for a $1.8 billion valuation, with Advance Publications remaining the majority stakeholder. In February 2019, a $300 million funding round led by Tencent brought the company's valuation to $3 billion. In August 2021, a $700 million funding round led by Fidelity Investments raised that valuation to over $10 billion.
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