6 months ago
Base Salary
$230k - $322k/yr
Responsibilities
- Architect, build, deploy, and operate large-scale ML systems for recommendations, search, messaging, and content understanding.
- Lead initiatives through ideation, modeling, experimentation, production deployment, and iteration.
- Design and improve recommender systems and ranking models across feeds, search, and notifications.
- Build AI-powered search and recommendation experiences, including LLM-integrated systems.
- Develop content pipelines, embeddings, and representation models for users, communities, and content.
- Use LLMs and multimodal models for understanding and personalization while evaluating performance, reducing bias, and improving accuracy.
- Partner with Product, Data Science, Infrastructure, Engineering, and UX teams to deliver user and business impact.
- Translate ambiguous business needs into scalable ML solutions.
- Mentor engineers, establish ML development and experimentation best practices, and act as a technical thought leader across teams.
Requirements
- At least 6 years of experience building, deploying, and operating machine learning systems in production.
- Strong programming skills in Python, Go, or similar languages, with solid software engineering fundamentals.
- Strong knowledge of machine learning algorithms spanning statistical learning and deep learning architectures.
- Hands-on experience with modern ML frameworks such as PyTorch and TensorFlow.
- Experience designing scalable ML pipelines, data processing systems, and model-serving infrastructure.
- Experience driving measurable impact through applied machine learning and translating ambiguous product or business problems into technical solutions.
- Preferred expertise in recommender systems, search and ranking, advertising or auction systems, representation learning, multimodal embeddings, or content understanding.
- Preferred familiarity with distributed systems and large-scale data processing frameworks such as Spark, Kafka, Ray, Airflow, BigQuery, and Redis.
- Experience with real-time, low-latency production systems, feature engineering, model optimization, and production monitoring is preferred.
- Experience with LLM and generative AI techniques, including evaluation, alignment, fine-tuning, knowledge distillation, RAG or agentic systems, and productionizing LLM-powered products is preferred.
- An advanced degree in Computer Science, Machine Learning, or a related quantitative field is preferred.
Benefits
- Comprehensive healthcare benefits and income replacement programs.
- 401(k) with employer match.
- Global benefits supporting workspace, professional development, caregiving, family planning, gender-affirming care, and mental health and coaching.
- Flexible vacation, paid volunteer time off, and generous paid parental leave.
- Remote role, as indicated by the #LI-Remote designation.
- U.S.-based employees receive medical, dental, and vision insurance and other benefits.
Tech Stack
Categories
About Reddit
Reddit builds a social news and discussion platform organized into user-created forums (“subreddits”) for consumers, creators, and communities. It monetizes primarily through advertising tools for brands and self-serve advertisers, plus a Premium subscription; developers can access data via its API. Founded in 2005 and headquartered in San Francisco, Reddit became a public company on the NYSE in 2024 and hosts over 100,000 active communities.