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1 week ago
This role blends deep AI research with hands-on system development, ensuring you can conduct research, build, validate, and ship groundbreaking AI capabilities end-to-end.
You're a bridge between science and software. You'll innovate on large language models, prompt systems, evaluation frameworks, and algorithm pipelines—and bring them to production-grade systems that power real users.
Expect to author experimental prototypes rich enough for academic-quality write-ups, then productize those same ideas into robust, reliable software.
Key Responsibilities:- Tackle experiments in LLM training, LLM agent architectures, fine-tuning, reinforcement learning, and new evaluation methodologies.
- Build code-first prototypes to test hypotheses and iterate rapidly—refactor them into production systems when experiments succeed.
- Master's or Ph.D. in CS, ML, or related (or equivalent experience)
- Deep familiarity with LLMs, fine-tuning, reinforcement learning
- Expert in Python + frameworks like PyTorch or JAX; experience with Hugging Face or deployed LLM APIs
- Strong software engineering intuition: modular design, CI/CD, containerization, automated testing
- R&D code drives real product features—high user adoption, improved reliability or performance.
- Experimental pipelines and prototypes are production-ready within sprint cycles; clean codebases, smooth deployments, few bugs.
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