Staff AI Performance Engineer, Crusoe Energy Systems
$204-247k
+ Restricted Stock Units + Bonus
3 days a week in office (Sunnyvale, CA)
Renewable-powered AI infrastructure
Job no longer available
Renewable-powered AI infrastructure
1001+ employees
Job no longer available
$204-247k
+ Restricted Stock Units + Bonus
3 days a week in office (Sunnyvale, CA)
1001+ employees
Company mission
To accelerate the abundance of energy and intelligence.
Role
Who you are
- Expertise in CUDA or OpenCL – Demonstrated experience developing CUDA kernels or equivalent technologies
- Proficiency in Python – Strong programming skills, particularly in Python, for AI and performance optimization tasks
- Experience with deep learning frameworks – Hands-on knowledge of training infrastructure such as PyTorch or TensorFlow
- Strong understanding of CPU & GPU architecture – Ability to analyze and optimize performance at the hardware level
Desirable
- Zero-to-Hero mindset – Experience taking a project from initial concept to full implementation
- Experience with vector instructions – Understanding of SIMD, AVX, or similar vector processing techniques
- Graphics shader knowledge – Background in graphics shaders as a proxy for CUDA expertise
What the job involves
- Crusoe Energy is on a mission to align the future of computing with the future of the climate. As a Staff AI Performance Engineer, you will play a pivotal role in optimizing scalable inference engines to enhance performance, efficiency, and speed.
- Your contributions will directly impact Crusoe’s revenue model, as faster inference translates to greater token throughput and increased efficiency in our AI infrastructure.
- If you are passionate about accelerating AI workloads, optimizing inference engines, and pushing the boundaries of high-performance computing, this role is for you
- This is a full-time hybrid role based in San Francisco, CA, or Sunnyvale, CA, requiring in-office presence three times a week
- Optimize inference engines – Improve inference performance in engines such as VLLM, ensuring maximum efficiency and scalability
- Enhance scalable AI infrastructure – Implement optimizations that accelerate AI inference, directly impacting Crusoe’s efficiency and revenue generation
- Develop CUDA kernels – Write and deploy CUDA kernels to optimize deep learning workloads, improving computational performance
- Conduct performance analysis – Profile and analyze training and inference workloads to identify and resolve bottlenecks
- Engage with the AI research community – Track developments in scalable inference, contribute to open-source projects, and publish research to advance the field
- Improve onboarding and documentation – Enhance internal documentation and tooling standards to streamline team workflows and training
- Collaborate cross-functionally – Work closely with AI researchers, engineers, and infrastructure teams to develop cutting-edge solutions
Our take
Crusoe is tackling one of the biggest challenges facing the digital age: the enormous energy demand of data centres and AI infrastructure. As AI models grow more powerful, they require immense computing power (and therefor electricity) to train and operate. This surge in energy use has put some pressure on power grids, driven up costs, and raised environmental concerns. Crusoe is on a mission to make this process more sustainable by finding smarter, cleaner, and more efficient ways to power the data centres that drive modern computing.
The company started out by putting wasted energy to work. Originally known as Crusoe Energy, it captured natural gas that would otherwise be burned off ("flared") at remote oil sites and used it to power modular data centres. Today, Crusoe has evolved into a major player in AI infrastructure, designing and operating large-scale data centres near renewable or stranded energy sources. It's now one of a handful of "neocloud" companies (next-generation cloud providers focused on flexible, efficient computing for AI workloads). And its facilities are helping tech giants like OpenAI handle the massive computing requirements of training advanced AI models.
Recently, Crusoe has attracted some huge investor attention, tripling its valuation to over $10B and raising almost $1.4B in its 2025 funding round. It's building OpenAI's first major US data centre campus and even experimenting with bold new frontiers. In partnership with Starcloud, Crusoe plans to deploy the world's first space-based cloud computing infrastructure, powered by solar energy and orbiting the Earth by 2027. If successful, this could redefine how and where computing happens, opening up a cleaner, virtually limitless source of energy for AI's next generation.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 6 rounds)
Oct 2025
$1.4bn
SERIES E
Dec 2024
$600m
SERIES D
Total funding: $2.5bn
Company benefits
- Health & wellbeing: Comprehensive health benefits designed to support your overall wellness
- Time away: Paid time off for vacations, family bonding, and unexpected needs
- 401(k) match: Build your financial future with our 401(k) matching program
- Mental wellness: Resources and support for your emotional wellbeing and navigating life's challenges
Company HQ
Union Station, Denver, CO
Leadership
Cully Cavness
(Co-Founder, COO & President)Began their career as an Energy Infrastructure Research Fellow before spending 3 years as a Business Development Manager at Recurrent Engineering and serving as CFO of Sword & Plough. They left their role as VP of Highlands Natural Resources to co-found Crusoe Energy Systems.
Chase Lochmiller
(Co-Founder & CEO)Prior to co-founding Crusoe in 2018, Chase was a General Partner at Polychain Capital, a Quantitative Trade at Jump Trading Group, and a Managing Director of Algorithmic Trading at KCG Holdings.
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