Training, Process Management Engineer
Build and optimize Rust- and Python-based distributed systems that orchestrate, monitor, and debug machine-learning workloads across extremely large supercomputing clusters. The role emphasizes performance, correctness, reliability, observability, and fault tolerance.
About the job
Responsibilities
- Work across Python and Rust stacks.
- Design, build, and maintain software to orchestrate and monitor machine learning workloads on large supercomputers.
- Profile and optimize the software stack for computation orchestration at frontier scale.
- Improve reliability, observability, and fault tolerance for long-running jobs.
- Debug complex distributed-systems issues across large clusters.
- Respond to changing ML-system requirements to enable researchers.
Requirements
- Experience developing distributed systems.
- Strong software engineering skills and proficiency in Python and Rust or another systems programming language such as C++.
- Solid Linux knowledge.
- Experience with systems-level debugging, performance analysis, and memory profiling.
- Experience developing asynchronous and concurrent systems.
- Interest in performance, correctness, reliability, and large-scale system behavior.
- Comfort working in high-ownership environments with light process and strong engineering agency.
Benefits
- Hybrid work model with three days per week in the office.
- Relocation assistance for new employees.
Skills
Python, Rust, C++, Linux, Distributed Systems, Asynchronous Systems, Concurrent Systems, Performance Analysis, Memory Profiling, Fault Tolerance
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