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, visit www.redditinc.com . 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. You don’t need experience in every area listed below. A background in a few may make you a great fit! 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 #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit redditinc.com . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Requirements

Must-haves

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.
You don’t need experience in every area listed below. A background in a few may make you a great fit!
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
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 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
This job posting may span more than one career level.

Nice-to-haves

Experience writing production-quality code, including testing, evaluation, and monitoring; Python experience required, Golang experience a plus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaimlllmpythongolang

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

401(K)

Parental Leave

Professional Development