Machine Learning Engineer, Answers Relevance

12h•$216,700 - $322,000•Remote

About The Position

Reddit’s Answers Relevance team uses AI to connect people with knowledge and conversations from Reddit communities. The team is hiring Senior and Staff Machine Learning Engineers to make Answers more relevant and helpful. In this role, you will lead machine learning projects from concept through production and partner with Product, Data Science, and Engineering across recommendations, search, messaging, and AI systems. Relevant areas may include recommendation systems, search, content understanding, ML infrastructure, retrieval-augmented generation, LLM evaluation and features, agentic AI, open-weight models, model quality and safety, and product evaluation.

Requirements

4–12 years of experience building, deploying, and operating machine learning systems in production.
Broad knowledge of machine learning fundamentals and experience applying them in production; expert-level modeling depth is not 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 is required.
Experience with machine learning 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.

Nice To Haves

Golang experience.
Experience in one or more of recommendations, search, content understanding, or large-scale data and ML infrastructure.
Experience with large-scale recommendation systems or foundational retriever models.
Experience with RAG systems, retrieval methods, LLM evaluation, or production LLM features.
Experience with agentic AI, such as tool calls, MCPs, multi-agent systems, or orchestration.
Experience with self-hosted open-weight models such as Qwen or Llama, including prompt engineering, fine-tuning, post-training, or prompt optimization.
Experience improving grounding, instruction following, and hallucination, and evaluating retrieval and generation quality.
Experience scaling LLM systems, including latency, caching, cost, and safety measures for prompt injection and unsafe inputs.
Experience defining product success metrics, feedback loops, and evaluation approaches, including human review.

Responsibilities

Build and improve large-scale machine learning systems, including retrieval and ranking, embeddings, and LLM-powered features.
Set technical direction and deliver measurable user and business impact.
Partner with other teams to shape product and technical roadmaps.
Evaluate new AI/ML approaches and support responsible LLM development.
Mentor engineers and contribute to long-term machine learning planning.
Lead machine learning projects from idea to production in collaboration with Product, Data Science, and Engineering.

Benefits

Comprehensive healthcare benefits and income replacement programs.
401(k) with employer match.
Global benefit programs supporting workspace, professional development, and caregiving.
Family planning support.
Gender-affirming care.
Mental health and coaching benefits.
Flexible vacation and paid volunteer time off.
Generous paid parental leave.
Equity in the form of restricted stock units; depending on the position offered, commission may also be available.
Medical, dental, and vision insurance for U.S.-based employees.