Staff Applied ML Engineer, Federal/National Security

We need to output HTML fragment with sections: About the role, Responsibilities (What You'll Do), Requirements (What We're Looking For), maybe Benefits, Pay, Schedule if present. The posting includes Salary Range, Benefits, Location, Clearance/Eligibility. We need to include sections only if real content. We must not repeat job title as heading. Use

for each section heading. We need to preserve all substantive info, remove boilerplate like About Us, Clearance/Eligibility? Actually Clearance/Eligibility is substantive; we could include it maybe under a section like "Clearance & Eligibility" but not in prescribed list. The instruction says use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but says "Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It implies we should use those headings when applicable. For clearance/eligibility maybe we can put under Requirements or Qualifications. Could incorporate into Requirements. Location maybe not a heading; could be a paragraph. We need to include Pay section because salary range given. Benefits section because benefits described. Schedule? Not given, so omit. We need About the role section: from "About The Role" paragraph. Responsibilities: "What You'll Do" bullet list. Requirements: "What We're Looking For" bullet list. Qualifications maybe not separate; we could combine with Requirements. Skills: maybe list from deep expertise bullet. But we can keep Requirements as bullet list; maybe also include Skills as separate if we want. However instruction: prefer few substantive sections over many thin ones. So we could have About the role, Responsibilities, Requirements, Benefits, Pay. That's five sections. We need to include location and clearance maybe within Requirements or About the role? Could add a short paragraph after About the role? But we must not invent headings. Could add a

after About the role containing location and clearance info. That's allowed. We must not include boilerplate like Equal Opportunity Employer, Applicant Data Disclosure, etc. Remove those. We must preserve all substantive information: include details about building production LLM-powered applications, etc. Include bullet points exactly as given. We need to format bullet lists with

• . Let's extract content. About The Role paragraph: "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." That's the About the role. What You'll Do (Responsibilities) list: - Build production LLM-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 (Requirements) list: - 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 paragraph (maybe could be part of About the role or separate but we can incorporate into About the role? It's motivational; we could keep as a paragraph under About the role or separate "Why This Role" but not required heading. Could add as a

  after About the role. 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: "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: "Salary Range: $180,000-240,000 + bonus + equity. This represents the typical salary range for this position based on experience, skills, and other factors." Benefits: list bullet points. We need to include Benefits section with those bullet points. Let's extract benefits: - 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 should not include the Equal Opportunity Employer etc. Now construct HTML. We'll have:

  About the role

  ... (About The Role paragraph + Why This Role paragraph + Clearance/Eligibility + Location maybe as separate sentences)

  But we might want to keep clearance and location as separate

  after About the role? The instruction says use

  for prose. So we can have multiple

  elements. We need to avoid repeating job title. Let's structure:

  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.

  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.

  Then Responsibilities:

  Responsibilities

  • Build production LLM-powered applications, AI agents, and agentic workflows
  ...
  Requirements:

  Requirements

  • 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
  But we have nested list; that's okay. Benefits:

  Benefits

  • 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.
  Pay:

  Pay

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

  We should not include Schedule. Now ensure we didn't include any boilerplate like Equal Opportunity, Applicant Data Disclosure, etc. Check that we preserved all substantive info: About Us? Not needed. The "About Us" paragraph is not required; we can drop as it's boilerplate? It's about the firm; maybe considered substantive but not required heading. The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. "About Us" is not explicitly listed but could be considered boilerplate? It's about the firm; maybe we can keep but not required. However we already have About the role; we could keep About Us as a paragraph but not under a heading. The instruction says preserve ALL substantive information; do NOT invent or summarize away detail. About Us is substantive about the firm. Should we include? It might be considered boilerplate but it's descriptive of the company. The instruction didn't explicitly say to remove About Us; only cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we could keep About Us as a paragraph before About the role. But we already have About the role heading; we could add a

  about the firm before that. However the instruction says "use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule