Senior/Staff AI Engineer

DDN

AI Engineer responsible for developing and optimizing infrastructure for production AI systems. Focused on performance for large-scale GPU and CPU environments in a leading data intelligence company.

Posted 5/15/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $150,000 - $250,000 per yearWebsite

Tech Stack

Tools & technologies

Distributed Systems

About the role

Key responsibilities & impact

Build and optimize LLM serving and inference systems for production environments
Improve performance across GPU and CPU pathways
Work on KV cache, memory, storage, and throughput bottlenecks
Design and scale systems that support RAG and retrieval-heavy AI workloads
Contribute to infrastructure where storage architecture and systems efficiency materially affect AI performance
Solve engineering problems at the intersection of AI, high-performance systems, and distributed infrastructure

Requirements

What you’ll need

An engineer who has spent meaningful time building or optimizing production AI systems, not just experimenting with models
Someone who understands how inference performance is shaped by the interaction between compute, memory, storage, and serving architecture
Deep hands-on experience working close to the systems layer — for example, improving how workloads run across GPU and CPU resources, reducing bottlenecks, or tuning infrastructure for better throughput and latency
Evidence of real ownership in areas like model serving, retrieval, caching, storage, or distributed performance, rather than purely application-layer AI work
The ability to move comfortably between architecture decisions and hands-on implementation, especially in environments where efficiency and scale matter
A background that suggests you can operate in technically demanding environments, whether that comes from AI infrastructure, high-performance systems, storage platforms, or adjacent distributed systems work
PhD preferred, but far less important than having built serious systems in the real world.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account DDN Website LinkedIn All Job Openings 1001 - 5000 employees Founded 1998 🤖 Artificial Intelligence 💰 $10M Funding Round on 2011-06 Artificial Intelligence
Data Center and Cloud Computing
High Performance Computing DDN is a global leader in AI data intelligence solutions, providing high-performance computing and sophisticated data management technologies. With a focus on accelerating AI deployments and advanced data analytics, DDN's products, including the Data Intelligence Platform and advanced storage systems, serve diverse sectors such as healthcare, financial services, and government. DDN is committed to transforming enterprise data infrastructure to leverage the full potential of AI and drive operational efficiency. Senior/Staff AI Engineer 🔥 8 minutes ago 🏄 California – Remote 💵 $150k - $250k / year ⏰ Full Time 🟠 Senior 🤖 AI Engineer 🦅 H1B Visa Sponsor Distributed Systems Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Build and optimize LLM serving and inference systems for production environments
Improve performance across GPU and CPU pathways
Work on KV cache, memory, storage, and throughput bottlenecks
Design and scale systems that support RAG and retrieval-heavy AI workloads
Contribute to infrastructure where storage architecture and systems efficiency materially affect AI performance
Solve engineering problems at the intersection of AI, high-performance systems, and distributed infrastructure 🎯 Requirements
An engineer who has spent meaningful time building or optimizing production AI systems, not just experimenting with models
Someone who understands how inference performance is shaped by the interaction between compute, memory, storage, and serving architecture
Deep hands-on experience working close to the systems layer — for example, improving how workloads run across GPU and CPU resources, reducing bottlenecks, or tuning infrastructure for better throughput and latency
Evidence of real ownership in areas like model serving, retrieval, caching, storage, or distributed performance, rather than purely application-layer AI work
The ability to move comfortably between architecture decisions and hands-on implementation, especially in environments where efficiency and scale matter
A background that suggests you can operate in technically demanding environments, whether that comes from AI infrastructure, high-performance systems, storage platforms, or adjacent distributed systems work
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Applicant Tracking System Keywords

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Hard Skills & Tools

LLM servinginference systemsGPU optimizationCPU optimizationKV cachememory managementstorage architecturethroughput optimizationAI performance tuningdistributed systems

Soft Skills

problem-solvingownershiparchitecture decision-makinghands-on implementationadaptabilitycollaborationtechnical communicationefficiency focusscalability awarenessoperational capability

Certifications

PhD in relevant field