Software Engineer

Responsibilities: Architect, design, build and maintain the distributed high performance engine that supports our real-time machine learning inference pipeline Investigate and develop fault tolerance mechanisms to improve reliability of client installs Coordinate with internal teams for feature requirements, integration, deployment constraints and reliability Optimize data serialization methods to improve training times and usability by other teams. Write property, integration, unit, performance regression tests. Optimize hardware utilization (CPU, GPU, Memory)

Requirements: Rust Distributed systems and fault tolerance Deep knowledge of Linux systems programming: IO multiplexing, socket programming, memory mapped IO, etc Expert level experience with concurrency primitives: threads, semaphores, mutexes and their tradeoffs Lock-free and wait-free data structures Functional design patterns

Nice to have: x86-64 Architecture Memory consistency models CUDA/OpenCL Experience High performance computing Edge computing Experience with cluster schedulers/resource managers such as Mesos, Slurm, Torque or Kubernetes Experience with parallel programming tools such as MPI, Spark, actor models like Erlang or Akka Python