About Us

Red Cell Partners is an incubation firm building and investing in rapidly scalable technology-led companies that are bringing revolutionary advancements to market in three distinct practice areas: healthcare, cyber, and national security. United by a shared sense of duty and deep belief in the power of innovation, Red Cell is developing powerful tools and solutions to address our Nation’s most pressing problems.

About Stealth Startup

We're launching a new startup that is redefining how mission-critical organizations adopt AI. Our platform helps organizations across healthcare, government, and other regulated industries transform institutional knowledge into intelligence assets that improve the accuracy, reliability, and impact of AI in real-world workflows. We're a fast-moving team of builders, researchers, and operators working to help customers create, measure, and continuously improve AI capabilities they can own and control.

About the Role

We are seeking a Member of Technical Staff, AI Researcher to help turn complex, real-world workflows into the evaluation frameworks, reinforcement learning environments, and feedback systems needed to advance frontier AI.

This is a blended research and engineering role for someone who operates at the intersection of scientific inquiry and technical execution. You will investigate how data, evaluations, and feedback systems influence model behavior, while building the infrastructure and tools required to test and apply those ideas.

Responsibilities

Design and build evaluation frameworks, benchmarks, and methodologies for frontier large language models, AI agents, multimodal models, and reinforcement learning environments
Develop reward models, programmatic verifiers, graders, and other feedback systems that make model behavior measurable and improvable
Design and run controlled supervised fine-tuning and reinforcement learning experiments to measure the effects of datasets on model capability, generalization, and alignment
Research and define what makes evaluations representative of real-world work and operational environments
Build systems for producing high-quality human data, including expert task design, annotation methodologies, data-quality signals, and data-attribution techniques
Translate research questions into lightweight, rigorous experiments that generate actionable findings
Prototype quickly, evaluate results, diagnose failure modes, and convert findings into improved benchmarks, datasets, or technical systems
Move promising methods from experimentation into scalable, production-quality implementations
Work across research, engineering, product, and operations to advance a shared technical roadmap
Contribute to the broader technical community through benchmarks, open-source tools, research, and technical writing

This Role is a Great Fit if You

Are equally comfortable investigating an open-ended research question and building the system needed to test it
Approach AI research with a builder mindset and focus on producing measurable, usable outcomes
Are deeply interested in how data structure, selection, attribution, and quality affect model behavior
Can design focused experiments, interpret imperfect or ambiguous results, and translate findings into technical decisions
Are eager to move quickly without sacrificing rigor, maintainability, or engineering quality
Are comfortable working across unfamiliar domains and converting real-world workflows into measurable tasks
Demonstrate high agency, sound technical judgment, and a strong sense of ownership
Communicate complex technical concepts clearly to both technical and nontechnical stakeholders
Are comfortable operating in a fast-moving environment where priorities and technical approaches may evolve
Are motivated by the purpose and real-world impact of the work, not simply by access to emerging technologies

Skills & Qualifications

5+ years of relevant experience in machine learning, artificial intelligence, computer science, data science, software engineering, or a related technical field