Staff Software Engineer, Enterprise GenAI & Scale

Scale AI; New York (NY); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health & wellbeing

Career growth

Community & events

Parental support

Job summary

Scale AI is looking for a strong engineer to join our team in New York, owning large areas of our product and collaborating across backend and frontend. You will interact with LLMs and ML models, solving hard engineering problems in scalability and reliability, and delivering experiments at high velocity to engage customers.

You will work across the entire product lifecycle, from conceptualization through production, and must be willing to rapidly learn new technologies in a fast-paced

Qualifications

• 7+ years of full-time engineering experience.
• Strong understanding of software engineering principles.
• Experience with large-scale distributed systems.
• Proficient in Python or JavaScript/TypeScript and SQL.
• Experience with major cloud providers (AWS, Azure, GCP).
• Experience with Kubernetes.
• Experience tinkering with or productizing LLMs, vector databases, and AI technologies.

Responsibilities

• Own large new areas within Scale AI's product.
• Work across backend, frontend, and with LLMs and ML models.
• Deliver experiments at high velocity and quality.
• Contribute through the entire product lifecycle from concept to production.
• Be able to multi-task and learn new technologies quickly.

Skills

Distributed systems

Python

JavaScript/TypeScript

SQL

Cloud platforms (AWS/Azure/GCP)

Kubernetes

LLMs / vector databases

AI productization

Tools

AWS

Azure

GCP

Kubernetes

Vector databases

Job description

Scale AI is looking for a strong engineer to join our team in New York, owning large areas of our product and collaborating across backend and frontend. You will interact with LLMs and ML models, solving hard engineering problems in scalability and reliability, and delivering experiments at high velocity to engage customers.

You will work across the entire product lifecycle, from conceptualization through production, and must be willing to rapidly learn new technologies in a fast-paced