1 ml infrastructure engineer job at 1 company in Eudora, KS

PromotedHiringCafe
ML Engineer - Inference & Model Deployment
Cupertino, CA, US
$250k-$310k/yr On-SiteFull Time
HiringCafe
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Turn powerful AI and ML models into fast, reliable production systems. Own inference latency, throughput, model-serving architecture, multi-GPU systems, and production deployment for millions of users.
Python, PyTorch, vLLM, SGLang, TensorRT, LLMs
PromotedHiringCafe
Founding Machine Learning / AI Search Engineer
Cupertino, CA, US
$160k-$310k/yr On-SiteFull Time
HiringCafe
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Build the ML and AI search behind HiringCafe — ranking, recommenders, retrieval, and LLM agents that surface jobs people would never find on their own.
Python, PyTorch, Elasticsearch, LLMs
PromotedHiringCafe
Founding Backend / Infra Engineer
Cupertino, CA, US
$160k-$300k/yr On-SiteFull Time
HiringCafe
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Own the crawlers, pipelines, and infrastructure powering a real-time job search engine. Strong Node.js and Python fundamentals; bonus points for security and reverse-engineering chops.
Node.js, Python, Elasticsearch, Redis
3w
Save
Mark Applied
Hide
AI Solutions Architect - Central Region
Chicago or Detroit or Minneapolis or St. Louis or Kansas City or Omaha or Columbus or Tulsa or Nashville or Austin
$185k-$235k/yr FieldFull Time
World Wide Technology
World Wide Technology: Global technology solutions provider and systems integrator.
10+ YOE10+ years in technical pre-sales/solutions architecture; hands-on AI/ML infrastructure design across GPU, storage, networking and MLOps; NVIDIA and cloud platform experience; bachelor's degree required; strong presentation and whiteboarding skills.
NVIDIA DGX, NVIDIA HGX, CUDA, AI Enterprise, NeMo, Omniverse, Advanced Technology Center (ATC), AWS, Azure, GCP, Dell, HPE, Cisco, NetApp, Pure Storage, Vast Data, MLOps