Crusoe designs, builds, and operates energy-first AI infrastructure. Its offerings include Crusoe Cloud for GPU-based training, fine-tuning, inference, and managed services, alongside AI-optimized data centers and energy infrastructure.

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Skills

C#Cuda Docker Gpu Inference Kubernetes Llm Machine Learning Optimization Profiling Python Sglang Vllm

Candidate Availability

Onsite · San Francisco · Required

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will lead a hands-on engineering team that optimizes large-language-model inference for production. You will profile and improve serving performance, develop production software, tailor customer deployments, and guide work from proof of concept through monitored production operation.

Requirements

2+ years of experience managing and leading an engineering team in a high-performance or ML-focused environment
Hands-on software engineering, low-level optimization, or ML infrastructure experience
Experience shipping production code in Python or C++, with Python preferred
Knowledge of high-throughput, low-latency LLM inference optimization
Experience with vLLM or SGLang and kernel-level performance profiling
Knowledge of GPU architecture and behavior
Experience with large language models and AI/ML development and deployment pipelines
Communication skills for explaining technical topics to customers and teammates

Responsibilities

Bring current inference techniques into production and refine them
Design and optimize serving architectures, including prefill and decode disaggregation and request routing
Profile the serving stack and resolve performance problems down to CUDA kernels
Adapt and scale optimization methods across ML models, especially large language models
Tune deployments for latency, throughput, cost, and reliability
Tailor deployments with customer engineering teams from proof of concept to monitored production
Build and support production software and product features around the inference stack
Run experiments, define specifications, and ship well-tested results
Lead delivery from experiments to production optimizations and establish performance goals
Partner on technical strategy and roadmaps

Benefits

Equity packages
Restricted Stock Units
Paid time off, paid holidays, and leave programs
Health, dental, and vision insurance
Employer HSA contributions
Paid parental leave
Life insurance and short-term and long-term disability insurance
Tuition reimbursement
Mental health and wellness support
Commuter benefits
Cell phone stipend
401(k) with company match up to 4% of salary
Volunteer time off
Global travel insurance and emergency assistance
Daily meals allowance