10 days ago
Base Salary
$170k - $205k/yr
Responsibilities
- Design and operate reliable managed AI services for serving and scaling LLM workloads.
- Build automation and reliability tooling for distributed AI pipelines and inference services.
- Define, measure, and improve SLIs/SLOs across AI workloads.
- Collaborate with AI, platform, and infrastructure teams to optimize large-scale training and inference clusters.
- Build telemetry and performance-tuning strategies for latency-sensitive AI services.
- Investigate and resolve reliability issues in distributed AI systems using telemetry, logs, and profiling.
- Contribute to next-generation distributed systems designed for AI-first environments.
Requirements
- Strong software engineering background building production-grade systems beyond scripting or Bash.
- Demonstrated experience designing and implementing distributed systems.
- Hands-on experience with large language models or AI/ML infrastructure.
- Experience defining and measuring SLIs/SLOs, building monitoring and observability systems, improving performance and reliability, designing fault-tolerant systems, and developing automated testing strategies.
- Proficiency in at least one of Python, Go, Java, or C++.
- Familiarity with Kubernetes or container orchestration platforms.
- Strong collaboration and communication skills and the ability to work in a fast-paced, mission-driven environment.
- Experience scaling LLM inference or training workloads is a bonus.
Benefits
- Industry-competitive pay and restricted stock units.
- Health insurance options including HDHP and PPO, plus vision and dental coverage for employees and dependents.
- Employer HSA contributions, paid parental leave, paid life insurance, and short- and long-term disability coverage.
- Teladoc, a 401(k) with a 100% match up to 4% of salary, generous paid time off, and a holiday schedule.
- Cell phone reimbursement, tuition reimbursement, and a Calm app subscription.
- MetLife Legal and a company-paid commuter benefit of $300 per month.
Tech Stack
Categories
ML EngineeringSite Reliability
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.