Investigate and mitigate performance bottlenecks in large-scale distributed training and inference systems.
Develop and implement low-level (operator/kernel) and high-level (system/architecture) optimization strategies.
Translate research models and prototypes into highly optimized, production-ready inference systems.
Explore and integrate inference compilers such as TensorRT, ONNX Runtime, AWS Neuron and Inferentia.
Design, test, and deploy scalable solutions for parallel and distributed workloads on heterogeneous hardware.
Facilitate knowledge transfer and bidirectional support between Research and Engineering teams, ensuring alignment of priorities and solutions.
Collaborate closely with Research and Engineering teams to bridge research and production engineering.
Requirements
Strong expertise in the Python ecosystem and major ML frameworks (PyTorch, JAX).
Experience with lower-level programming (C++ or Rust preferred).
Deep understanding of GPU acceleration (CUDA, profiling, kernel-level optimization); TPU experience is a strong plus.
Proven ability to accelerate deep learning workloads using compiler frameworks, graph optimizations, and parallelization strategies.
Deep understanding of modern deep learning systems, including layer-level optimization, large-scale distributed training, streaming, low-latency and asynchronous inference, inference compilers, and advanced parallelization techniques.
Solid understanding of the deep learning lifecycle: model design, large-scale training, data processing pipelines, and inference deployment.
Strong debugging, profiling, and optimization skills in large-scale distributed environments.
Excellent communication and collaboration skills, with the ability to clearly prioritize and articulate impact-driven technical solutions.
Experience with inference compilers such as TensorRT, ONNX Runtime, AWS Neuron, Inferentia, or similar technologies.
Benefits
Fully remote team
Competitive salary range: $240,000 - $275,000
Compensation, benefit, and other reward opportunities
Commitment to pay equity
Inclusive, equal opportunity workplace
ATS Keywords
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