Hiring: AI Research Scientist Company: Noösphere Location: Greater Seattle Area Job Posted Time: 2026-09-16 00:04:43 Target Skills & Keywords : Computer Vision, Elasticsearch, Kind, Machine Learning, Move About the job Required Skills: •Human-centered physical intelligence starts with •models that learn from how people actually do things in the real world •. Our systems run in homes and workplaces with people doing real tasks, and every deployment returns hours of continuous, time-synchronized multimodal data. Nothing comparable exists publicly, and the models and benchmarks for this kind of data have yet to be built. •We're looking for an experienced researcher to be a driving force behind this work: shaping what these models should be capable of and building the evals that measure it, pretraining and post-training multimodal foundation models on our data, and shipping them into systems operating in the real world, where telemetry returns within days and shapes what we collect next. Research is what moves the company forward. The models we train determine what our systems can do, and the benchmarks we build define how we judge progress. •What You'll Do •Design and run the eval suite •Design the eval suite that measures the capabilities we care about over real-world input, and stand it up as a repeatable, versioned system the whole team runs against. •Build novel evals for tasks without an established benchmark, with metrics tied to real-world usefulness. •Extend evals beyond offline benchmarks to online evaluation of how models actually behave in deployment, where static metrics stop being predictive. •Analyze failure modes, red-team behavior, and turn results into concrete priorities for data and training. •Train, deploy, and study models •Post-train multimodal foundation models on our data — SFT, RL, and preference optimization — and design experiments that isolate what improves performance. •Take models from research into production — export, optimization, and inference across edge and cloud targets under real-time constraints — and build the telemetry that feeds failures and edge cases back into the data engine. •Prototype agentic systems that perceive, reason, and act over continuous multimodal input, both in real time and offline over recorded data. •Run scaling-law studies — how capability moves with data volume, diversity, model size, and compute — and use them to shape the research and data roadmap. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!