Staff Software Engineer, Data Platform
Scale AI · San Francisco, CA | New York City, NY · Horizontals EPD
About this role
Scale AI is hiring a staff-level Software Engineer based in San Francisco, CA | New York City, NY. The posting calls out experience with Kubernetes, Docker, PostgreSQL, MongoDB. Compensation is listed at $252,000–$315,000 per year.
- Role
- Software Engineer
- Function
- software engineering
- Level
- staff
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY
- Department
- Horizontals EPD
More roles at Scale AI
Job description
from Scale AI careersSoftware is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.
At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.
At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.