2 months ago
Base Salary
$250k - $300k/yr
Responsibilities
- Bring modern LLM inference optimization techniques into production.
- Design and optimize serving architectures, including prefill/decode disaggregation and request routing.
- Profile and improve serving frameworks such as vLLM and SGLang down to the kernel level.
- Tune deployments for latency, throughput, cost, and reliability under real traffic.
- Adapt deployments to customer models and constraints and guide workloads from proof of concept to monitored production service.
- Build and support production software and product features around the inference stack, primarily using Python or other general-purpose languages.
- Run focused experiments, define specifications and proofs of concept, and ship well-tested optimizations.
- Own delivery from initial experimentation through production deployment and collaborate on feature and product requirements.
- Make sound tradeoffs concerning system complexity, tooling, and implementation decisions.
Requirements
- Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.
- Production coding experience in one or more general-purpose languages, such as Python or C++, with Python preferred.
- Hands-on familiarity with methods for optimizing LLMs for high-throughput and low-latency inference.
- Experience with LLM serving frameworks such as vLLM or SGLang and with kernel-level performance profiling and analysis.
- Strong understanding of GPU architecture and behavior.
- Hands-on interest and experience with large language models.
- Working knowledge of AI/ML pipelines and the development and deployment lifecycle for ML models.
- Strong communication skills for explaining complex technical topics to customers and teammates.
- Preferred experience making software systems faster, especially LLM systems; CUDA or comparable technologies; software engineering fundamentals; AI/ML inference systems; Docker; Kubernetes; and customer-facing AI/ML projects.
Benefits
- Competitive compensation and equity packages, including Restricted Stock Units.
- Paid time off, paid holidays, and leave of absence programs.
- Comprehensive health, dental, and vision insurance.
- Employer HSA contributions.
- Paid parental leave.
- Paid life insurance and short- and long-term disability coverage.
- Professional development and tuition reimbursement.
- Mental health and wellness support.
- Commuter benefits for parking and transit.
- Cell phone stipend.
- 401(k) retirement plan with company match up to 4% of salary.
- Volunteer time off.
- Global travel insurance and emergency assistance.
- Daily meals allowance and additional location-specific perks and programs.
Tech Stack
Categories
About Crusoe
Crusoe builds and operates GPU-powered data centers and an AI cloud platform for enterprises running large-scale AI training and inference. It vertically integrates energy supply with compute, using stranded and renewable power to reduce emissions and costs, and sells capacity via cloud services and managed infrastructure. Founded in 2018 and headquartered in Denver, the company is privately held.