Scale AI

Senior Software Engineer, Full-Stack - Scale GP

$216K–$270KFull-time · San Francisco, CA +1 more
✓ Verified live on the employer's own system · added 248 days ago
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Mid-level · 5+ yrs exp

Requirements

Experience: 5+ years

Skills & tools

Frontend DevReactJavascriptPythonDistributed SystemsMachine LearningDevopsCloud Platforms
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Full job description

We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack-from React/TypeScript frontends to Python-based backends-while integrating with LLMs and machine learning systems.

You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment.

- Own major full-stack product areas , driving features from design through production deployment.

- Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness.

- Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components.

- Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences.

- Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers.

- Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP.

- Adapt quickly -learning new technologies, frameworks, and tools as needed across the stack.

- 5+ years of full-time engineering experience , post-graduation.

- Strong experience developing full-stack applications using React, TypeScript, and Python .

- Experience scaling or shipping products at high-growth startups .

- Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome).

- Experience with Kubernetes , containerization, and microservice architectures.

- Experience working with at least one major cloud provider (AWS, GCP, or Azure).

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