Senior Staff Applied AI Inference Engineer

The role

You will make large language models run faster, cheaper, and more reliably in production by owning the inference stack end to end. This involves profiling, applying optimization techniques, and working with customer engineering teams to tailor deployments.

What you will do

• Bring current inference techniques into production and refine them.
• Design and optimize serving architectures.
• Work down into the serving stack from frameworks to CUDA kernels.
• Adapt and scale optimization methods across many kinds of ML models.
• Profile and tune deployments against latency, throughput, and cost targets.
• Tailor deployments to customer models and constraints.
• Build and support software and product features around the inference stack.
• Experiment quickly to find what works and ship well-tested results.
• Own delivery end to end from experiment to production.
• Work through ambiguity and make sound calls on tradeoffs and tooling.

Required qualifications

• Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.
• Hands-on experience shipping code in production with one or more general-purpose languages, such as Python or C++.
• Familiarity with methods for optimizing LLMs for high throughput / low latency inference.
• Comfort with modern LLM serving frameworks such as vLLM or SGLang, and with profiling and analyzing performance down to the kernel level.
• A firm grasp of how GPUs are built and how they behave.
• Clear interest and hands-on experience with large language models.
• A working knowledge of AI/ML pipelines and the full path of developing and deploying ML models.
• Strong communication skills.

Nice to have

• A track record of making software systems run faster, especially for large language models.
• Experience with CUDA or comparable technologies.
• A strong command of software engineering fundamentals, with a record of building and shipping AI/ML inference systems.
• Experience with Docker and Kubernetes.
• Prior work building or tuning AI/ML projects, particularly in a customer-facing setting.

Benefits

• Competitive compensation and equity packages
• Restricted Stock Units
• Paid time off, paid holidays & leave of absence programs
• Comprehensive health, dental & vision insurance
• Employer contributions to HSA account
• Paid parental leave
• Paid life insurance, short-term and long-term disability
• Professional development & tuition reimbursement
• Mental health & wellness support
• Commuter benefits (parking & transit)
• Cell phone stipend
• 401(k) Retirement plan with company match up to 4% of salary

About the company

Crusoe is a vertically integrated AI infrastructure company that owns and operates each layer of the stack to power AI workloads. They use an energy-first approach to solve the demand for AI compute and power bottlenecks.