AI Performance Engineer: Scale ML Training & Inference

applied; Sunnyvale (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Applied Intuition, Inc. in Sunnyvale, California, is seeking a performance engineer to optimize large-scale ML workloads in the data center.

You will focus on distributed training across many nodes and high-throughput offline processing of petabyte-scale sensor logs to enable faster iteration. You will profile across the stack, identify bottlenecks, and close the gap between theoretical and actual performance, collaborating with teams across accelerators, ML frameworks, and data infrastructure

Qualifications

• Hands-on ML performance engineering experience: profiling, roofline analysis, throughput optimization, and root-cause investigation.
• Experience with distributed multi-node training at scale (FSDP, DeepSpeed, Megatron, NCCL, or equivalent).
• Deep familiarity with GPU or accelerator performance concepts - memory bandwidth and kernel launch overhead.
• Experience with high-throughput or batch inference systems (NVIDIA Triton, TensorRT, ONNX Runtime, Ray).
• Fluency in Python and proficiency in C++ or another systems language.
• Excellent debugging, analytical, and problem-solving skills.
• A deep understanding of machine learning foundations and ability to develop technical solutions.

Responsibilities

• Profile and optimize distributed training end to end across data loading, preprocessing, kernels, and communication.
• Optimize large-scale offline and batch inference over petabyte-scale sensor logs.
• Establish roofline models and rank optimization opportunities by impact.
• Improve multi-node scaling: sharding, communication, interconnect utilization, memory bandwidth.
• Drive cluster goodput by reducing GPU idle time due to pipeline stalls and I/O gaps.
• Build benchmarking, observability, and regression-detection tooling.
• Collaborate with engineers across functions to solve data and compute problems at scale.
• Contribute to a culture of collaboration, technical excellence, and innovation.

Skills

ML performance

Distributed training

GPU performance

Batch inference

Python & C++

Debugging skills

ML foundations

Tools

NVIDIA Triton

TensorRT

ONNX Runtime

Ray

Nsight Systems/Compute

Job description

Applied Intuition, Inc. in Sunnyvale, California, is seeking a performance engineer to optimize large-scale ML workloads in the data center.

You will focus on distributed training across many nodes and high-throughput offline processing of petabyte-scale sensor logs to enable faster iteration. You will profile across the stack, identify bottlenecks, and close the gap between theoretical and actual performance, collaborating with teams across accelerators, ML frameworks, and data infrastructure