2 days ago
Kuwait City, KuwaitMid Level
Responsibilities
- Own implementation, testing, and delivery of defined AI components within established system designs.
- Build agent tools, model integrations, backend services, and APIs.
- Run and extend evaluations, interpret results, investigate model failure modes, and flag regressions.
- Debug production issues and resolve them using team engineering practices.
- Manage delivery dates within scope and communicate progress, blockers, and trade-offs early.
- Work directly with client teams on requirements and feedback.
- Share learnings and develop public-sector domain expertise.
Requirements
- Experience building and shipping production software.
- Proficiency in Python and working knowledge of at least one of TypeScript, Java, or C++.
- Hands-on experience integrating models or AI/ML components into production applications, such as calling LLMs, building retrieval or agent tooling, or deploying trained models.
- Working understanding of ML evaluation, including reading results, spotting regressions, and identifying common causes of model failure.
- Experience owning defined work through testing, release, and production debugging.
- Strong problem-solving, data-driven iteration, written communication, and verbal communication skills.
- Preferred: backend or full-stack engineering background and experience across API, service, and data-schema layers.
- Preferred: experience with AWS, GCP, or Azure cloud ML platforms.
- Preferred: exposure to agentic workflows, retrieval-augmented generation, or context engineering.
- Preferred: experience handling regulated or sensitive data.
Categories
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.