Staff Applied ML Engineer, Federal/National Security

Red Cell Partners

• $180K — $240K *
US-Anywhere
+ 2 other locationsRemote
Aerospace & Defense
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in building ML or AI systems with a focus on production deployment
  • Hands-on experience with advanced LLMs and foundation models
  • Deep knowledge in LLM fine-tuning, model evaluation, or RAG systems
  • Expertise in agentic systems with a focus on tool use
  • Proficient in model serving, inference, and knowledge retrieval
  • Ability to bridge the gap between ML experimentation and production engineering
  • Familiarity with ambiguous technical problems and operational workflows

Responsibilities

  • Build production applications powered by LLMs and AI agents
  • Develop and manage model evaluation, fine-tuning, and experimentation pipelines
  • Decide on the appropriate use of prompting, RAG, or fine-tuning techniques
  • Create robust evaluation systems for model quality and reliability
  • Develop retrieval systems for both structured and unstructured data
  • Optimize models and inference systems for real-world applications
  • Continuously improve models based on user feedback and performance metrics
  • Collaborate with Forward Deployed Engineers and customers to translate mission needs into AI capabilities

Benefits

  • Career advancement opportunities with strong performance
  • 100% employer-covered health care benefits for employees and families
  • 14 weeks of paid maternity and paternity leave
  • Unlimited PTO, subject to management approval
  • Opportunities for professional development and continued learning
  • Optional 401K, FSA, and equity incentives
  • Mental health support services through Tara Mind
  • Affordable GLP-1 solutions via Crux
Full Job Description
About the Role

Red Cell Federal is hiring a Staff Applied ML Engineer to build and deploy production AI systems for federal and national security missions.

You'll work across LLMs, model fine-tuning and adaptation, agentic systems, RAG, evaluation, and inference, helping turn rapidly evolving AI capabilities into reliable software that operates in real mission environments.

This isn't a pure research role, and it isn't an ML infrastructure role removed from users. You'll work alongside Forward Deployed and Software Engineers, occasionally directly with customers, to understand operational problems and determine how models, data, agents, and software can solve them.

Red Cell Federal's platform is being designed to support interchangeable models, including specialized smaller models for edge use cases, and to operate across cloud, on-premise, and edge environments.
What You'll Do
  • Build productionLLM-powered applications, AI agents, and agentic workflows
  • Develop and own model evaluation, fine-tuning, adaptation, and experimentation pipelines
  • Determine when to use prompting, RAG, fine-tuning, specialized models, or combinations of these approaches
  • Build rigorous eval systems for model and agent quality, reliability, tool use, and task completion
  • Develop retrieval and context systems across structured and unstructured mission data
  • Optimize models and inference for production environments
  • Deploy and improve models based on real-world performance and user feedback
  • Partner with FDEs and customers to translate mission requirements into production AI capabilities
  • Turn solutions developed for individual deployments into reusable platform capabilities
What We're Looking For
  • Significant experience building ML or AI systems and deploying in production
  • Hands-on experience with modern LLMs and foundation models
  • Deep expertise in several of the following:
    • LLM fine-tuning / model adaptation
    • Model evaluation
    • RAG and retrieval systems
    • Agentic systems and tool use
    • Model serving / inference
    • Embeddings and knowledge retrieval
    • Synthetic data
    • Guardrails and AI reliability
  • Ability to move comfortably between ML experimentation and production engineering
  • Ability to operate independently against ambiguous technical problems
  • Interest in working close to users and seeing how AI performs against real operational workflows
Why This Role

The challenge here isn't proving that an LLM can perform a task. It's figuring out how to make AI reliable enough to use in production, measurable enough to know when it fails, adaptable enough to improve quickly, and practical enough to operate within real national security environments.

Red Cell Federal is focused on that "agentic last mile": operationalizing and deploying AI against mission requirements rather than stopping at decision support or prototypes.

If you want to work deeply on the models and stay close enough to the problem to see whether what you built actually works, let's talk!
Clearance / Eligibility

Because this role supports federal and national-security customers, U.S. citizenship is required with an Active Secret or Top-Secret Security Clearance.
Location

Washington, DC / Northern Virginia preferred. This role may require regular customer-facing work, including onsite meetings, secure-facility work, or travel depending on program needs.

Salary Range: $180,000-240,000 + bonus + equity. This represents the typical salary range for this position based on experience, skills, and other factors.

#LI-RCP

Our Red Cell Partners Benefits (may differ for each incubation):

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.

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