Senior AI Inference Engineer: High-Throughput LLMs

Crusoe Energy Systems; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Paid time off

Mental wellness support

Job summary

Crusoe Energy Systems in San Francisco is hiring an ML systems engineer focused on making large language models run faster, cheaper, and more reliably in production. You will own the end-to-end inference stack, profiling time and cost, and bringing modern optimization techniques to real deployments.

The role involves hands-on coding, low-level optimization, and collaboration with customer engineering teams to tailor deployments to their workloads and latency targets.

Qualifications

• Proven experience shipping production-grade ML inference systems.
• Strong background in optimizing LLMs for latency and throughput.
• Experience profiling kernels and serving stacks for performance.
• Comfort with customer-facing discussions and requirements.

Responsibilities

• Own end-to-end optimization of inference stacks for evolving models.
• Profile, tune, and debug performance across GPUs and kernels.
• Collaborate with customers to tailor deployments and monitor results.
• Lead experiments from concept to production with measurable gains.

Skills

Production code

LLM optimization

Performance profiling

Customer-facing

Python

Communication skills

AI/ML pipelines

Education

Bachelor/Master/PhD in CS or related

Tools

CUDA

Docker

Kubernetes

vLLM

SGLang

Job description

Crusoe Energy Systems in San Francisco is hiring an ML systems engineer focused on making large language models run faster, cheaper, and more reliably in production. You will own the end-to-end inference stack, profiling time and cost, and bringing modern optimization techniques to real deployments.

The role involves hands-on coding, low-level optimization, and collaboration with customer engineering teams to tailor deployments to their workloads and latency targets.