Foundational Model Research Data Scientist

Foundational Model Research Data Scientist

Seattle, WA or US Remote

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share.

The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that.

Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves.

Let’s achieve more, together.

This is a research role focused on the models at the foundation of collective intelligence. You study, adapt, and advance the foundational models that power how Sapience AI understands language, knowledge, and reasoning.

You work where research meets the platform: designing experiments, evaluating models, adapting them to the demands of professional communities, and feeding what you learn into the COGENT architecture and MINERVA.

You bring scientific rigor to a fast-moving field, and you turn that rigor into advances the product can actually use.

The quality of collective intelligence depends on the models beneath it. How well the platform understands a community’s language, grounds its answers, and reasons over knowledge starts with foundational model work done well.

The field moves quickly, and not every advance is real or ready. Someone has to separate genuine progress from noise and turn the real advances into something the platform can rely on.

The Foundational Model Research Data Scientist does that. You run the experiments, evaluate honestly, and translate frontier progress into dependable capability for Sapience AI.

You hold seven areas of responsibility across foundational model research. Each one is yours to set direction on, build, and measure.

• Design and run experiments on foundational models relevant to collective intelligence.
• Investigate how models understand language, ground answers, and reason over knowledge.
• Turn open questions into experiments with clear hypotheses and honest results.

• Adapt foundational models to the language and needs of professional communities, including fine-tuning and alignment where it helps.
• Improve grounding and reduce confident errors in domain settings.
• Balance capability against cost, latency, and the constraints of production.

• Build rigorous evaluation for what matters here: accuracy, groundedness, safety, and trust.
• Design evaluations that reflect real community needs, not just public benchmarks.
• Keep the organization honest about what a model can and cannot do.
• Partner with data engineering on the datasets that training and evaluation depend on.
• Handle data thoughtfully, including quality, bias, and protection of sensitive community knowledge.
• Build the evidence base that makes model claims defensible.

• Feed model advances into the neuro-symbolic COGENT architecture, and study how neural and symbolic methods work together.
• Help decide where a foundational model belongs and where structure should carry the load.
• Turn research into behavior the platform can rely on.

• Track the fast-moving foundational model field and separate real progress from hype.
• Bring in advances that…