Performance Engineer
Anthropic
- Running machine learning (ML) algorithms at our scale often requires solving novel systems problems
- As a Performance Engineer, you’ll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems
- Implement low-latency high-throughput sampling for large language models
- Implement GPU kernels to adapt our models to low-precision inference
- Write a custom load-balancing algorithm to optimize serving efficiency
- Build quantitative models of system performance
- Design and implement a fault-tolerant distributed system running with a complex network topology
- Debug kernel-level network latency spikes in a containerized environment
Benefits
- Comprehensive health, dental, and vision insurance for you and your dependents
- Inclusive fertility benefits via Carrot Fertility
- 22 weeks of paid parental leave
- Flexible paid time off and absence policies
- Mental health support for you and your dependents
- Competitive salary and equity packages
- Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
- Retirement plans with competitive matching
- Life and income protection plans
- $500/month flexible wellness and time saver stipend
- Commuter benefits
- Annual education stipend
- Home office stipends
- Relocation support for those moving for Anthropic
- Daily meals and snacks in the office
Want to learn more about machine learning researchHave significant software engineering or machine learning experience, particularly at supercomputing scaleCare about the societal impacts of your workAre results-oriented, with a bias towards flexibility and impactPick up slack, even if it goes outside your job descriptionEnjoy pair programming (we love to pair!)High performance, large-scale ML systemsGPU/Accelerator programmingOS internalsML framework internalsLanguage modeling with transformersStrong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also
#J-18808-LjbffrReference: WJ-766_22186539