Scientist 

Job Description

Responsibilities

• Track advancements in LLM and generative model research, and translate them into concrete opportunities for the problem space we are working on.
• Apply state-of-the-art techniques to high-impact problems such as summarization quality and building LLM-based evaluators (“judges”) that assess whether generated content meets quality bars.
• Lead end-to-end ML development on these problems: research, model training, and evaluation.
• Partner with ML scientists and engineers to integrate models into business applications and platforms.
• Translate complex technical concepts for both technical and non-technical stakeholders to inform strategic decisions.
• Act as a subject matter expert, working cross-functionally to identify high-impact opportunities and define and execute roadmaps.
• Engage with the ML community, internal and external, to learn, to teach, and to contribute to building a great brand.

About you

• Demonstrated habit of tracking the LLM/generative model literature and a knack for spotting which advances are relevant to real business problems.
• Strong foundation in ML and Deep Learning, especially in Natural Language Processing / Understanding and Generation. Research experience in summarization or generated-text evaluation (e.g., LLM-as-judge methods) is a big plus; background in vision models such as diffusion models is a plus.
• Expertise in one or more LLM post-training approaches.
• Track record of designing, running, and analyzing rigorous experiments — from hypothesis formation through statistical validation of results

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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