Principal Applied ML Researcher (Agentic Systems & Applied AI Platform)

Confirmed live in the last 24 hours

Red Cell Partners

Compensation

$230,000 - 300,000

Seattle, WA or McLean, VA or Remote

Hybrid

Posted April 6, 2026

Job Description

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 Trase

Co-founded in 2023 by Joe Laws and Grant Verstandig, Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings. Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security.

About the Role

As a Principal Applied ML Researcher, you will define and drive the ML and LLM strategy for Trase OS, the agentic execution platform powering deployments in regulated environments.

You are responsible for how models behave inside real production systems - including agent workflows, tool use, and long-lived execution -not just offline model performance.

This is a hands-on technical leadership role operating at the intersection of research, systems, and product. You will drive technical breakthroughs in agentic infrastructure and applied AI systems, own the end-to-end research-to-production lifecycle, and set the standard for how ML systems are designed, evaluated, and deployed across Trase.

Why This Role Exists

Trase OS coordinates long-lived agents, multi-step workflows, tool-augmented LLMs, and execution in regulated environments.

As the system scales, the core challenge shifts from model capability to system correctness and reliability, where models may succeed offline but fail in real workflows, agent behavior can become unpredictable or unsafe, evaluation can drift from real outcomes, and ML decisions can introduce system-level instability.

This role defines how ML systems are integrated into execution

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