Staff Machine Learning Engineer, Ads ML Efficiency
New
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Reddit, Inc.Machine learning infrastructure
Location: Remote - United StatesFull-TimeStaff
SalaryThe base salary range for this position is: $230,000 — $322,000 USD
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Job Details
- Experience
- 5+ years of software engineering experience.
- Required Skills
- PythonJavaC++GoRustDistributed Systems
Requirements
- Hold a BS, MS, or PhD in Computer Science or a related field.
- Have 5+ years of software engineering experience.
- Have strong proficiency in Python.
- Have experience building distributed systems at scale.
- Have experience with machine learning infrastructure, training systems, or model serving platforms.
- Have a deep understanding of performance engineering and systems optimization.
- Have strong debugging and profiling skills.
- Proficiency in at least one systems language (Go, C++, Rust, or Java) is preferred.
- Experience with large-scale recommendation, ranking, generative AI, or foundation model systems is preferred.
- Experience with distributed training frameworks such as PyTorch Distributed, Ray, TensorFlow, or Spark is preferred.
- Familiarity with GPU architectures and performance analysis tools is preferred.
- Experience optimizing cloud infrastructure costs across large ML workloads is preferred.
- Experience building real-time ML inference applications is preferred.
Responsibilities
- Design and build systems that improve the efficiency of ML training and inference workloads.
- Develop tooling to help 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.
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