Machine Learning Engineer, Answers Relevance

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From “How do I fix a leaky faucet?” to “What should I watch next?”, the Answers Relevance team leverages AI to connect people with the real-world wisdom of Reddit communities. We’re hiring Senior and Staff Machine Learning Engineers to make Answers smarter, more relevant, and more helpful. Our SOTA AI systems helps surface the right conversations, but the heart of Answers is still people helping people ~ Redditors sharing what they know with each other!

What You’ll Work On
You’ll lead ML projects from idea to production, partnering with Product, Data Science, and Engineering across recommendations, search, messaging, and AI systems.

• Recommendations, search, content understanding, or large-scale data and ML infrastructure
• SOTA large scale RecSys 
• Foundational retriever models
• RAG systems, retrieval methods, LLM evaluation, or production LLM features
• Agentic AI, such as tool calls, MCPs, multi-agent systems, or orchestration
• Self-hosted open-weight models such as Qwen or Llama; prompt engineering, fine-tuning, post-training, or prompt optimization
• Improving grounding, instruction following, and hallucination; evaluating retrieval and generation quality
• Scaling LLM systems, including latency, caching, and cost; safety measures for prompt injection and unsafe inputs
• Defining product success metrics, feedback loops, and evaluation approaches, including human review

What You’ll Do

• Build and improve large-scale ML systems, including retrieval and ranking, embeddings, and LLM-powered features
• Set technical direction and deliver measurable user and business impact
• Work with partner teams to shape product and technical roadmaps
• Evaluate new AI/ML approaches and support responsible LLM development
• Mentor engineers and contribute to long-term ML planning

Required Qualifications

• 4–12 years of experience building, deploying, and operating ML systems in production
• Broad knowledge of ML fundamentals and experience applying them in production; expert-level modeling depth isn’t required
• Experience developing and productionizing models with TensorFlow, PyTorch, or Hugging Face Transformers
• Experience writing production-quality code, including testing, evaluation, and monitoring; Python experience required, Golang experience a plus
• Experience with ML systems such as data pipelines, feature engineering, model training and serving, and production monitoring
• Strong communication and collaboration skills, and a record of delivering measurable product impact

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