Remote Staff ML Engineer - Ads Efficiency & Platform

Engg; United States; Remote; USD 230,000 - 322,000; Full time

Benefits offered by this job

Global benefits program

Family planning support

Mental health & coaching

Private medical and dental

401(k) with employer match

Generous paid time off

Parental leave

Job summary

Reddit is a community of communities. The ML Efficiency team builds infrastructure and tooling to help ML engineers train, evaluate, deploy, and operate models at scale.

You will focus on improving productivity, reducing costs, and accelerating experimentation across the ML ecosystem. The role involves designing high-performance systems, benchmarking, and collaborating with researchers to drive optimization across distributed training and inference workflows, with opportunities to impact

Qualifications

• Required BS, MS, or PhD in Computer Science or a related field.
• 5+ years of software engineering experience.
• Strong proficiency in Python.
• Proficiency 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.

Responsibilities

• Design and build systems that improve the efficiency of ML training and inference workloads.
• Develop tooling that helps ML engineers debugging, 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.

Skills

Python

Go/C++/Rust/Java

Distributed systems

ML infrastructure

Performance engineering

Debugging & profiling

GPU architectures

Education

CS degree (BS/MS/PhD)

Tools

PyTorch Distributed

Ray

Tensorflow

Spark

Job description

Reddit is a community of communities. The ML Efficiency team builds infrastructure and tooling to help ML engineers train, evaluate, deploy, and operate models at scale.

You will focus on improving productivity, reducing costs, and accelerating experimentation across the ML ecosystem. The role involves designing high-performance systems, benchmarking, and collaborating with researchers to drive optimization across distributed training and inference workflows, with opportunities to impact