Staff Machine Learning Engineer (ML Efficiency)

Location: Remote from the United States or Canada

Base salary: $230,000–$322,000 USD per year, plus potential equity and commission depending on the position offered.

Company

Reddit operates a large online community platform with more than 100,000 active communities and approximately 130 million daily active unique visitors.

What you will do

• Design and build systems that improve the efficiency of machine learning training and inference workloads.
• Develop tooling for debugging, profiling, optimization, and monitoring of model performance.
• Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.
• 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 and define technical strategy for scalable, reliable, and cost-efficient ML platforms.

Requirements

• BS, MS, or PhD in Computer Science or a related field.
• 5+ years of software engineering experience.
• Strong proficiency in Python.
• Experience building distributed systems at scale and working with ML infrastructure, training systems, or model serving platforms.
• Deep understanding of performance engineering, systems optimization, debugging, and profiling.
• Proficiency in at least one systems language such as Go, C++, Rust, or Java is preferred.

Nice to have

• Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.
• Experience with PyTorch Distributed, Ray, TensorFlow, or Spark.
• Familiarity with GPU architectures and performance analysis tools.
• Experience optimizing cloud infrastructure costs across large ML workloads.
• Experience building real-time ML inference applications or internal platforms used by multiple ML teams.

Culture & Benefits

• Flexible remote-first workforce.
• Workspace, professional development, caregiving, family planning, and mental health support programs.
• Private medical and dental coverage, pension or 401(k) programs with employer matching, and income replacement programs.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.
• Interviews may be recorded, transcribed, and summarized by AI, with the option to opt out before scheduled interviews.