Join Reddit as a Staff Machine Learning Engineer to enhance ML efficiency and drive performance improvements across the platform.
Requirements
- Experience
- 5+ years
- Education
- Bachelor's degree
Benefits
Joblaze summary
The Staff Machine Learning Engineer for ML Efficiency at Reddit focuses on enhancing the efficiency of machine learning training and inference systems. This role requires strong skills in Python and a systems language, along with experience in building distributed systems and optimizing performance. Ideal candidates have a solid background in software engineering, particularly in machine learning infrastructure, and are well-versed in performance engineering. The position is part of a team dedicated to improving developer productivity and reducing costs across Reddit's extensive ML ecosystem.
Joblaze insights
- Listed today on Joblaze — tracked directly from Reddit's career page.
- Reddit has 172 other open roles including Senior SRE, Ads, Senior Manager, Large Customer Sales (Entertainment), Staff SRE, Ads.
- 2516 active Python roles on Joblaze right now.
- 816 active Go roles on Joblaze right now.
- 793 active Java roles on Joblaze right now.
Quick facts
- Is the Staff Machine Learning Engineer, ML Efficiency role remote?
- Yes — Reddit lists this as a fully remote position.
- How much experience is required?
- At least 5 years of relevant experience for this Staff Machine Learning Engineer, ML Efficiency role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, Ray, Spark, Java, Go, Rust.
- What seniority level is this role?
- Reddit targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Staff Machine Learning Engineer, ML Efficiency role at Reddit.
From the original posting
Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.
About the Team
The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem.
Responsibilities
- Design and build systems that improve the efficiency of ML training and inference workloads.
- Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
- Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.
- Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
- Build benchmarking frameworks and performance dashboards for training and serving systems.
- Optimize distributed training infrastructure, data pipelines, and model serving architectures.
- Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
- Drive technical strategy for ML platform scalability, reliability, and cost efficiency.
Qualifications
Required
- BS, MS, or PhD in Computer Science or a related field.
- 5+ years of software engineering experience.
- Strong proficiency in Python
- Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
- Experience building distributed systems at scale.
- Experience with machine learning infrastructure, training systems, or model serving platforms.
- Deep understanding of performance engineering and systems optimization.
- Strong debugging and profiling skills.
Preferred
- Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.
- Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
- Familiarity with GPU architectures and performance analysis tools.
- Experience optimizing cloud infrastructure costs across large ML workloads.
- Contributions to internal platforms used by multiple ML teams.
- Experience with building real time ML inference applications
What Success Looks Like
- ML engineers can move from idea to experiment faster.
- Training and inference costs decrease, performance increases, while model quality is maintained or improved.
- GPU utilization and cluster efficiency increase.
- Platform reliability improves as ML workloads scale.
- Teams spend less time managing infrastructure and more time building models.
- Average recommendation model size increases.
Benefits:
- 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
- Private Pension plan with Employer-matching
- 100% employer-sponsored group medical plan
- Income Replacement Programs
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
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.