Note: The job is a remote job and is open to candidates in USA. Yara is building an AI-powered platform to improve how people find work through professional profiles and smart matching. The Applied ML Engineer will build and own production LLM systems for real customers, including agent orchestration, tool use, retrieval, evaluations, and model-side engineering for trustworthy AI products in finance and enterprise settings.
Responsibilities
- You've shipped something LLM-powered that real people used, and you own the model side of it
- You know the difference between a wrapper and a system, because you've had to fix the wrapper
- You work well remotely: clear writing, async by default, and shipped work that speaks for you
- Your ML work sits on real engineering fundamentals, and interviews confirm it
- You want to work at the companies defining this wave, on the team that owns the models
Skills
- You've shipped something LLM-powered that real people used, and you own the model side of it
- You know the difference between a wrapper and a system, because you've had to fix the wrapper
- You work well remotely: clear writing, async by default, and shipped work that speaks for you
- Your ML work sits on real engineering fundamentals, and interviews confirm it
- You want to work at the companies defining this wave, on the team that owns the models
- 3 to 10 years in software or ML engineering with production LLM systems in the last two
- Python, plus strong fundamentals in TypeScript or Go
- Agent systems in production: orchestration, tool-calling, retrieval, evals, human-in-the-loop
- You're based in the US
- Links to anything agentic you've built
- Fine-tuning, distillation, or inference optimization experience is a strong plus
Benefits
- Remote work on teams across the US
- If not selected, continued access to Yara to list your work, browse millions of roles, manage your job search, and stay in the network for future opportunities
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