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NEXTMOVEFDE careers · United States
Labelbox

Forward Deployed Research Scientist

AI summary of the role

Forward Deployed Research Scientist at Labelbox builds and validates training data strategies for frontier AI labs via client engagements.

What you’ll do

  • . Fine-tune open-weight models on client data to measure impact of data on model performance.
  • . Engage in client scoping meetings to shape project specs via scientific data understanding.
  • . Review annotation schemas with ops team to ensure spec serves client training objectives.

What you’ll bring

  • . MS or PhD in Machine Learning, NLP, CS, or related quantitative field.
  • . Hands-on experience fine-tuning open-weight LLMs (Llama, Mistral, Qwen, etc.).
  • . Strong understanding of LLM training pipelines: pretraining, SFT, RLHF/DPO, data effects.

Technologies

Llama · Mistral · Qwen · RLHF · DPO · fine-tuning · LLM evaluation · reward modeling · open-weight models

About Labelbox

Three-pillar platform for frontier AI data: enterprise annotation tools, specialized labeling service (Alignerr), expert marketplace for model training and evaluation.

Series D

Source and classification

Deployment strategy · Evidence for this classification:

produce the training data that frontier AI labs use to build their most capable models. Our Forward Deployed Research Team sits at the intersection of research science and client delivery, embedding research capability directly into the engagements that drive our business. This is not a traditional research scientist role. You will not spend months pursuing a single research question. You will work on multiple client engagements simultaneously, operating on timescales of days to weeks. You will sit in scoping meetings with research teams at major AI labs, reason scientifically about data strategy in real time, fine-tune open-weight models to validate our data methodology, and collaborate with our Applied Research team to turn client-grounded findings into published work. The pace is fast, the problems are applied, and the feedback loops are short. We are looking for someone who finds
More from the job description

Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous G [... source excerpt omitted ...] on — we produce the training data that frontier AI labs use to build their most capable models. Our Forward Deployed Research Team sits at the intersection of research science and client delivery, embedding research capability directly into the engagements that drive our business. This is not a traditional research scientist role. You will not spend months pursuing a single research question. You will work on multiple client engagements simultaneously, operating on timescales of days to weeks. You will sit in scoping meetings with research teams at major AI labs, reason scientifically about data strategy in real time, fine-tune open-weight models to validate our data methodolo [... source excerpt omitted ...] applied, and the feedback loops are short. We are looking for someone who finds that energizing, not compromising. Your Impact Engage directly with frontier lab research teams. You will be in the room during client scoping meetings — not as support staff, but as a technical peer. You'll engage on methodology, challenge assumptions about data requirements, and shape project specifications based on a scientific understanding of how data composition affects model outcomes. Develop deep scientific understanding of client engagements. For each project, you will build a working model of the client's architecture, training methodology, and target capabilities. You'll use this unders

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