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Текст:
Hirify AI/Оригинал
TL;DR
Senior / Lead Research Scientist (AI): Developing best-in-class realtime multimodal models and the only realtime orchestration platform optimized for thousands of queries per second with an accent on training, new architectures, and scaling. Focus on evaluation, LLM-as-judge, and failure analysis.
Location: Germany. Future relocation to the San Francisco Bay Area may be supported with full U.S. visa and relocation assistance, subject to business needs and work authorization requirements.
Company
hirify.global is a research lab and inference provider building realtime AI systems, speech models, LLM-serving infrastructure, and modular APIs for high-volume consumer applications.
What you will do
Define and investigate open-ended research questions across foundation models, agents, multimodal systems, and realtime AI.
Design and run experiments involving model architectures, reinforcement learning, reward modeling, scaling, and test-time compute.
Build benchmarks, evaluation loops, quality measurement systems, and failure-analysis processes.
Develop research from initial hypothesis through experiments, written findings, and production deployment.
Collaborate with U.S.-based leadership and engineering teams to ship research into high-volume inference systems and APIs.
Requirements
Strong practical experience in enough of the relevant areas to demonstrate research ability and impact.
Experience with foundation models, evaluation, frontier AI topics, or related machine learning research.
Evidence of full-cycle research ownership, including framing questions, running experiments, writing results, and shipping outcomes.
Published research at venues such as ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI, or equivalent practical work.
PhD in machine learning or natural language processing, or equivalent practical experience.
Professional fluency in written and spoken English is required.
Nice to have
Non-trivial AI side projects, interdisciplinary experiments, open-source contributions, competitions, or other public work.
Experience with LLM-as-judge systems, world models, tool use, or agentic systems.
Culture & Benefits
Work on unclear problems with autonomy to define the direction and design the experiment.
Evaluation is treated as a first-class research product, with impact prioritized over publication volume.
Flat structure, fast iterations, and minimal process overhead.
Opportunities to share work that advances the field.
Potential U.S. visa and relocation support for candidates relocating to the San Francisco Bay Area, subject to business needs and legal requirements.
Hiring process
No cover letter is required; examples or links to work you have built are valued.
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