Level

Reddit

Machine Learning Engineer, Answers Relevance

Reddit is hiring a Machine Learning Engineer, Answers Relevance for a remote role open to applicants in United States. It pays $217k-$322k a year and Level rates it ; you can apply on Level.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • Pay on this posting starts 9% higher than the typical machine learning engineer posting on Level.
  • This is listed as a remote role.
  • The posting mentions Llama, Hugging Face and PyTorch among its tools and skills.
  • Reddit has 146 other open roles on Level.

AI in this role

Build and scale state-of-the-art machine learning systems, retrieval models, and LLM-powered features for Reddit's Answers Relevance team.

llamahugging-facepytorchtensorflowqwen
prompt-engineeringragfine-tuningai-evaluationmachine-learningrecsysllmpython
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 https://www.redditinc.com/careers/.

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.

How we rate this

Machine Learning Engineer, Answers Relevance at Reddit rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGFine-tuningAI EvaluationMachine learningRecsysLLMPython

Pay

This job starts at
$217k
Typical machine learning engineer job
$198k

This posting starts 9% above the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  4. How do you decide that one model's output is better than another's for a given task?
  5. Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, AI Evaluation, and Machine learning. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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