Pay
Higher than most similar jobs
$217K–$303K against $166K–$240K, the middle half of what similar US postings state.
From 1,319 postings in the last year. Stated ranges, not salaries paid.
Senior Machine Learning Systems Engineer
Remote - United States
Open 6 months, first seen by us 207 days ago- Pay
USD 216,700–303,400/year · BaseAnnual period assumed — pay source
The base salary range for this position is: $216,700—$303,400 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.
Read the full posting- Work setting
Remote — work setting source
Listed location: Remote - United States
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingDesign end-to-end MLOps patterns for data prep, model management, and experiment tracking
Build and support a graph ML codebase and platform from zero to one
Tune model training speed, efficiency, and GPU costs with ML engineers
Optimize batch data processing with Apache Beam, Spark, and Ray Data
Architect pipelines for graphs with billions of nodes and tens of billions of edges
From the employer’s posting
Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers
Zero-to-one development and support of a graph ML codebase and platform
Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs
Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more
Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges
Posting record
Report an errorOpen 6 monthsWe first saw this posting 207 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 14, 2026207 days ago
- Recorded sightings
- 373
- Last seen by us
- Nov 7, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 207
Up longer than most. Similar jobs usually come down between day 7 and day 71.
Well past Reddit’s usual: its jobs come down by about day 48.
From 4,682 similar postings that came down, and 33 of Reddit’s. Coming down is not always a hire.
Reddit is hiring
43 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is picking up
- Takes jobs down at a usual pace
- 2% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- BigQuery
- GCP
- Kubernetes
- MLflow
- Neo4j
- Spark
- Terraform
- PyTorch
- TensorFlow
- Google Cloud Storage
Where the posting names them
- Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes
- Hands-on experience with ML optimization, including memory and GPU profiling - Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb)
- Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle.
- Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc.
- Strong organizational & communication skills - Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus - Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus
- Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment - Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more - Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges
- Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus - Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus Pay Transparency:
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About Reddit
- People
- About 2,555 in 2025, up 14% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as RDDT.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.
What You’ll Do:
As a Senior ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit.
- Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more
- Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration
- Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment
- Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more
- Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges
Who You Might Be:
- 5+ years of experience in ML infrastructure, including model training and model deployments
- Hands-on experience with ML optimization, including memory and GPU profiling
- Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more
- Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb)
- Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc.
- Deep experience working with distributed training frameworks, including Ray and Kubernetes
- Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle.
- Strong organizational & communication skills
- Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus
- Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus
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—$303,400 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
The base salary range for this position is: $216,700—$303,400 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.
- Location & working pattern
Remote - United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.