Research Engineer
Crusoe
Job Overview
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Job Description
About Crusoe
Crusoe's mission is to accelerate the abundance of energy and intelligence. We're crafting the engine that powers a world where people can create ambitiously with AI — without sacrificing scale, speed, or sustainability.
Be a part of the AI revolution with sustainable technology at Crusoe. Here, you'll drive meaningful innovation, make a tangible impact, and join a team that’s setting the pace for responsible, transformative cloud infrastructure.
About This Role
We are looking for a Research Engineer to help design, evaluate, and productionize next generation AI inference systems. In this role, you will work at the intersection of applied research and real-world deployment, developing techniques that improve performance, efficiency, reliability, and cost of large-scale inference workloads.
You will collaborate closely with systems engineers, ML engineers, and infrastructure teams to drive research ideas toward impactful applications in real-world environments.
What You'll Be Working On
- Research, implement, and evaluate state-of-the-art techniques for AI inference, including areas such as speculative decoding, prefill–decode disaggregation, quantization, and kernel-level optimizations, with a focus on real-world customer use cases.
- Design and run experiments to understand trade-offs across latency, throughput, cost, and quality, and use these insights to guide system and model design decisions.
- Build and iterate on high-performance inference prototypes by translating research ideas into practical implementations, writing and optimizing performance-critical kernels, and improving low-level execution efficiency on modern accelerators.
- Analyze real-world inference workloads, identify opportunities for efficiency and scalability improvements, and stay current with advances in ML systems and inference research, sharing findings through internal reports and external contributions when appropriate.
- Define and contribute to the company road-map, impacting directly product and customers.
What You'll Bring to the Team
- Strong background in computer science, machine learning, or systems research.
- Ability to reason about performance at scale and work with real-world constraints.
- Comfortable collaborating across research, product and engineering teams.
- Familiarity with model inference concepts such as batching, quantization, kernels optimizations will be considered as advantages.
- Strong sense of ownership and the ability to drive ideas from concept through proof of concept.
- Independent individuals who thrive in challenging and ambiguous tasks with minimal supervision.
Benefits
Crusoe also offers a competitive benefits package designed to support financial security, health, and overall well-being. Our benefits are tailored to local market standards and include core offerings such as pension contributions and additional perks to support work-life balance.
Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Key skills/competency
- AI inference
- Machine Learning Systems
- Performance Optimization
- Scalability
- Quantization
- Speculative Decoding
- Kernel Optimizations
- Computer Science Research
- Experimentation Design
- Real-world Deployment
How to Get Hired at Crusoe
- Research Crusoe's mission: Study their commitment to sustainable energy and AI, values, and recent industry contributions.
- Customize your resume: Highlight experience in AI inference, ML systems, performance optimization, and large-scale computing.
- Showcase problem-solving: Prepare detailed examples of how you've designed, evaluated, and productionized complex technical solutions.
- Demonstrate collaboration: Be ready to discuss how you've worked effectively across research, product, and engineering teams.
- Understand AI systems: Prepare to discuss modern AI inference concepts, optimizations, and trade-offs in real-world scenarios.
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