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 systems, evaluated end-to-end, and operated reliably in production.

Responsibilities

Technical Leadership & Innovation

Drive technical breakthroughs in agentic systems, applied ML infrastructure, and LLM-based applications.
Define and evolve the ML/LLM strategy and technology roadmap in alignment with product development.
Act as a principal technical authority, making high-impact architectural and modeling decisions across teams.

Research → Prototype → Production

Develop prototypes for key technologies to validate new approaches and de-risk system design.
Own the full lifecycle from research and experimentation through production deployment, monitoring, and iteration.
Translate advances in ML into scalable, production-grade systems with measurable impact.

Agentic Systems & Applied ML

Design how LLMs operate within agent workflows, tool use, and multi-step reasoning and long-lived execution.
Implement and refine prompting strategies, multi-agent orchestration, memory management, and human-in-the-loop controls for safety and reliability.
Establish patterns for planning, decision-making, and tool orchestration within complex systems.

Evaluation, Quality & Reliability

Own end-to-end quality evaluation of ML-powered systems, including defining metrics, benchmarks, and testing frameworks.
Establish evaluation systems that connect model performance to task success and system-level outcomes.
Ensure systems behave predictably, safely, and reliably in production through monitoring, regression testing, and robust failure handling.

ML Systems & Platform Integration

Contribute to the design of ML systems supporting the full lifecycle, including training, fine-tuning, evaluation, deployment, and monitoring.
Drive architecture decisions across model serving, routing, orchestration, and latency and cost optimization.
Work across infrastructure layers, including cloud and containerized systems, to ensure scalable and efficient deployment.

Enterprise & Regulated Deployments

Build and deploy enterprise-grade AI systems used by global customers in production environments.
Design systems that operate reliably in regulated and constrained settings, including on-premise, air-gapped, and secure cloud environments.
Ensure systems are auditable, explainable, and compliant with regulatory and organizational requirements.

Communication & Influence

Write technical reports and design documents summarizing R&D progress, system behavior, and key decisions.
Communicate complex ML concepts and tradeoffs clearly to both technical and non-technical stakeholders.
Drive alignment across research, engineering, and product through strong technical leadership.

Mentorship & Organizational Impact

Mentor junior and senior engineers and researchers, raising the bar for ML rigor and system-level thinking.
Establish and propagate best practices for ML system design, evaluation, and reliability across the organization.
Influence technical direction beyond immediate teams through high-impact, cross-functional work.

Requirements

12–15+ years of experience in machine learning, including building and deploying applied ML systems in production environments.
Strong programming skills in Python, with experience in Java, C++, or related languages in systems contexts.
Deep expertise in at least one major ML domain, such as LLMs and generative AI, NLP or multimodal systems, deep learning, or graph learning.
Hands-on experience with prompt engineering, multi-agent orchestration, tool integration via APIs, memory management, and human-in-the-loop system design.
Proven experience building and shipping enterprise-grade AI systems, including GenAI, LLM, or agent-based applications at scale.
Experience designing and implementing evaluation frameworks, including metrics, benchmarks, and testing systems.
Strong understanding of ML system behavior in production, including reliability, latency, cost tradeoffs, and failure modes.
Experience deploying ML systems in regulated or constrained environments and familiarity with modern ML infrastructure such as cloud platforms and containerized systems.
Demonstrated ability to lead technical direction across teams and drive systems from concept to production impact.

Nice to Have

Experience working with agent-based systems, retrieval-augmented generation, RLHF, or synthetic data approaches.
Experience building and operating AI/ML platforms that support the full model lifecycle.
Experience optimizing ML inference in real-time, distributed, or resource-constrained environments.
Familiarity with data privacy, compliance, and responsible AI frameworks relevant to regulated industries.
Prior experience operating at the Staff or Principal level in a scaling organization.

Salary Range: $230,000-300,000. This represents the typical salary range for this position based on experience, skills, and other factors.

#LI-RCP

Our Red Cell Partners Benefits:

For full-time roles

Career track opportunity with potential for rapid advancement with strong performance as the firm grows
100% employer paid, comprehensive health care including medical, dental, and vision for you and your family.
Paid maternity and paternity for 14 weeks at employees' normal pay.
Unlimited PTO, with management approval.
Opportunities for professional development and continued learning.
Optional 401K, FSA, and equity incentives available.
Mental health benefits are available through Tara Mind.
Cost effective GLP-1 solutions available through Crux.

We’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.

Applicant Data Disclosure

By submitting an application, you acknowledge that Red Cell Partners, LLC ("Red Cell") uses third-party service providers to facilitate its recruitment and hiring processes. These providers include applicant tracking systems, candidate verification platforms, and fraud detection tools (collectively, "Hiring Platforms"). Your application materials, including your résumé, cover letter, work samples, responses to application questions, and any other information you submit, may be transmitted to and processed by these Hiring Platforms for the following purposes:

Managing and administering your application throughout the hiring process;

Verifying the accuracy and authenticity of application materials, including by cross-referencing information you provide against publicly available sources and proprietary databases;
Identifying indicators of potentially fraudulent, fabricated, or materially misleading application content, including but not limited to discrepancies between submitted materials and publicly available professional profiles, geographic anomalies, and fabricated work histories.

Applications that are flagged through this process as containing indicators of fraud or material misrepresentation may be declined from further consideration. If you have questions about the status of your application or the evaluation process, please contact talent@redcellpartners.com.

Red Cell requires its Hiring Platform providers to process your information solely for the purposes described above and in accordance with applicable law. Your information will be retained only for as long as necessary to fulfill these purposes and any applicable legal obligations, after which it will be deleted in accordance with Red Cell's data retention policies.

For more information about how your data is used, please refer to our Privacy Policy and Applicant Privacy Notice.

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

TLDR