Key skills
SQLAIMachine LearningMLLLMData EngineeringGKE
About this role
Role Overview
- Optimize Inference: Build and tune production LLM serving with vLLM and SGLang
- Profile & Accelerate Training: Instrument and profile training runs to find bottlenecks
- Engineer for the Hardware: Apply a working understanding of GPU architecture
- Serve at Scale: Deploy and operate multiple models within shared GPU clusters on GKE
- Drive Efficiency: Own GPU utilization as a first-class metric
- Collaborate & Consult: Work directly with clients to understand performance requirements
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
- 5+ years of experience in ML/AI engineering, with a meaningful portion focused on performance, infrastructure, or systems
- Proven track record of deploying and optimizing models in a production environment
- Demonstrated experience profiling and improving GPU utilization for training and/or inference
- Experience with Classic Machine Learning (neural nets, training, tuning) is a strong plus
- Knowledge of Data Engineering and SQL
Tech Stack
- SQL
Benefits
- Comprehensive Health Insurance
- Paid Leave (Vacation/PTO)
- Paid Holidays
- Sick Leave
- Parental Leave
- Bereavement Leave
- 401 (k) Employer Match
- Employee Referral Bonuses