Machine Learning Engineer, Answers Relevance

Reddit; Oregon; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Reddit is seeking Senior and Staff Machine Learning Engineers to advance the Answers platform. You will lead ML projects from idea to production across recommendations, search, and AI systems.

You will work with Product, Data Science, and Engineering to define roadmaps, evaluate approaches, and scale large-scale ML systems while emphasizing responsible AI and quality. You will mentor engineers and contribute to long-term ML strategy, building robust models and reusable components that impact

Qualifications

• 4-12 years of experience building, deploying, and operating ML systems in production.

Responsibilities

• Lead ML projects from idea to production across recommendations, search, and AI systems.
• Collaborate with Product, Data Science, and Engineering to shape roadmaps and evaluate approaches.
• Mentor engineers and contribute to long-term ML strategy.

Job description

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 130 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visitAt 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 teamleverages 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