Level

Reddit

Staff Machine Learning Engineer, Consumer

Reddit is hiring a Staff Machine Learning Engineer, Consumer for a remote role open to applicants in United States. It pays $230k-$322k a year and Level rates it ; you can apply on Reddit.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • The listed pay starts 15% above the typical machine learning engineer posting on Level.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include Hugging Face, PyTorch and TensorFlow.
  • Level lists 159 other open roles at Reddit.

AI in this role

hugging-facepytorchtensorflow
ragfine-tuningai-evaluationnlpai-research
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 powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact.

This role sits at the intersection of:

  • Relevance & recommendation systems (content, search, notifications)
  • AI-powered discovery & LLM-driven experiences
  • Content and user understanding & large-scale representation learning
  • Large-scale ML infrastructure and pipelines

What You’ll Do

  • Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions  
  • Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities  
  • Drive measurable impact on user engagement, discovery, and long-term value
  • Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities
  • Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge
  • Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment
  • Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing
  • Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making

Required Qualifications

  • 7+ years of experience building, deploying, and operating machine learning systems in production
  • Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc)
  • Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers
  • Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang
  • Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring
  • Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions
  • Track record of driving measurable impact through applied machine learning in real-world products

Preferred Qualifications

  • Subject matter expertise in one of the following domains:
    • Recommender systems
    • Search systems (lexical and semantic retrieval and ranking)
    • Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding)
  • Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
  • Experience working with real-time systems and low-latency production environments
  • Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
  • Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations
  • Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

  • Home Experience
  • ML Understanding
  • Feed Relevance
  • Answer Experience
  • Search and Answers Relevance
  • Search Experience

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:$230,000—$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

Staff Machine Learning Engineer, Consumer at Reddit rates 98 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. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGFine-tuningAI EvaluationNLPAI ResearchHugging FacePyTorchTensorFlow

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$230k
Typical machine learning engineer job
$199k

This posting starts 15% above the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. How do you decide that one model's output is better than another's for a given task?
  4. What NLP problem have you worked on, and how did you measure whether it actually worked?
  5. Tell me about a research question you investigated. What did you find?

Adapt your resume

  • List these exact terms on your resume: RAG, Fine-tuning, AI Evaluation, NLP, and AI Research. 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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