Adaption: Develops efficient AI systems that adapt in real-time.
5+ YOE5+ years in ML systems, inference infrastructure, or performance engineering; model-serving expertise; Python and systems-language proficiency; and GPU performance experience with measurable cost or latency improvements.
Inference Performance Engineer, AI Inference Configuration Optimization
Santa Clara or United States
$124k-$242k/yrHybridFull Time
NVIDIANASDAQ: NVDA: Designs GPU-accelerated computing and artificial intelligence hardware.
3+ YOEBachelor's, master's, or doctoral degree in a related field or equivalent experience; 3+ years' engineering experience; GPU profiling, Python, C++/CUDA, and AI inference optimization expertise required.
Material: Specialized inference cloud platform for high-performance AI workloads.
BS in CS/EE or related field; proficiency in Rust/Go/Python/C++; knowledge of concurrency, tail latency; experience with model serving; GPU/ASIC programming; low-precision inference; profiling and benchmarking.
Modular: Unified software infrastructure and programming language for AI development.
5+ YOE5+ years in distributed systems or performance engineering; experience building reusable tooling; strong technical judgment, communication, and leadership; GPU/kernel, inference engine, Kubernetes, and LLM familiarity helpful.
Machine Learning Performance Engineer - Offboard Training & Inference
Sunnyvale or Washington, D.C. or San Diego or Fort Walton Beach or Ann Arbor or London or Stuttgart or Munich or Stockholm or Bangalore or Seoul or Tokyo
$215k-$285k/yrOnsiteFull Time
Applied Intuition: Developing software and simulation infrastructure for autonomous vehicles.
ML performance engineering experience with distributed training, batch inference, GPU or accelerator optimization, Python, and C++ or another systems language; strong debugging and analytical skills required.
DigitalOceanNew York Stock Exchange: DOCN: Simplifies cloud infrastructure for developers, startups, and SMBs.
5+ YOE5+ years in high-performance computing or AI infrastructure, deep GPU and low-level optimization expertise, experience with CUDA/Triton/ROCm, distributed GPU parallelization, and system design for inference workloads.
LTIMindtreeNational Stock Exchange of India: LTIM: Global technology consulting and digital solutions.
8+ YOERequires 8+ years in infrastructure or ML engineering, hands-on NVIDIA GPU operations, Kubernetes GPU workloads, model serving, GPU scheduling and partitioning, KEDA autoscaling, and inference performance optimization.
Amazon Web Services (AWS), Amazon Elastic Kubernetes Service (EKS), AWS CloudFormation, NVIDIA AI Enterprise (NVAIE), NVIDIA GPU Operator, CUDA, Data Center GPU Manager (DCGM), NIM, NVIDIA Dynamo, OpenAI-compatible API, RunAI, Kubernetes, KEDA, NVIDIA Triton Inference Server, TensorRT-LLM, vLLM, NVIDIA Multi-Instance GPU (MIG), Amazon Outposts
TypeSafe AI: Building reliable, general frontier AI models for automation.
Deep CUDA/GPU kernel expertise, experience building and optimizing training and inference kernels, LLM training experience, profiling and eliminating performance bottlenecks.
LM Studio: Desktop software for running large language models locally and privately.
Significant production ML, inference runtime, or performance infrastructure experience; strong Python and C++; transformer and inference expertise; CPU/GPU profiling; PyTorch and inference system experience.
ByteDance: Developing AI-driven content platforms and mobile applications.
Bachelor's or master's degree in a technical discipline; proficient in C/C++, Python, CUDA, GPU architecture, deep learning operators, inference compilation, performance analysis, and distributed model inference.
RadixArk: Building scalable open-source infrastructure for AI training and inference.
Strong systems engineering in performance-critical software; GPU/distributed systems; profiling tools; Python and C++; CUDA/Triton/ROCm/XLA familiarity; LLM inference concepts; ability to debug across software, hardware, and infra layers; strong communication.
IntelNasdaq: INTC: Designs and manufactures microprocessors and semiconductor components.
8+ YOE8+ years software development; strong C++ and/or Python; experience with LLM inference, profiling and optimizing CPU/GPU performance; Linux and low-level debugging expertise.
Engram: Developing persistent memory layers for enterprise AI systems.
5+ YOE5+ years building training/inference systems; strong engineering skills; experience with ML frameworks, GPUs, distributed systems; bachelor's degree or equivalent experience.
Radical Numerics: Building general biological intelligence models for scientific discovery.
Deep expertise in large-model inference, GPU performance engineering, kernel development (CUDA/Triton), Python and PyTorch, distributed systems, and production model deployment.