Distributed ML Optimization Engineer

New

Skills

C++ CUDA Python Pytorch Rust

Join AssemblyAI as a Senior Research Engineer, working fully remote within the United States. You will drive performance and scalability in large-scale distributed training and inference for cutting-edge Speech AI models. Collaborate closely with both Research and Engineering teams to turn innovative prototypes into robust production systems, leveraging state-of-the-art technologies and frameworks.

Key Responsibilities
  • Investigate and resolve performance bottlenecks in distributed training and inference systems.
  • Design and implement optimization strategies at both operator/kernel and system/architecture levels.
  • Translate research models into highly efficient, production-ready inference systems.
  • Integrate inference compilers such as TensorRT, ONNX Runtime, AWS Neuron, and similar tools.
  • Deploy scalable solutions for parallel workloads on heterogeneous hardware.
  • Facilitate knowledge transfer and alignment between Research and Engineering teams.
Required Skills & Qualifications
  • Advanced expertise in Python and major ML frameworks (PyTorch, JAX).
  • Proficiency in lower-level programming languages (C++ or Rust preferred).
  • Strong background in GPU acceleration (CUDA, kernel-level optimization); TPU experience is a plus.
  • Hands-on experience with compiler frameworks, graph optimizations, and parallelization techniques.
  • Deep understanding of the deep learning lifecycle, including model design, training, data pipelines, and inference deployment.
  • Exceptional debugging, profiling, and optimization skills in distributed environments.
  • Excellent communication and collaboration abilities to support cross-functional teams.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: 12 Months

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