Lead Machine Learning Engineer (Level 4)

Nyla Technology Solutions

$220K — $250K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years in machine learning, MLOps, or data science
  • Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, or a related field
  • Active Top Secret clearance, SCI Eligible
  • Expertise in LangGraph for multi-agent orchestration
  • Hands-on experience with MLflow for model lifecycle management
  • Proficiency in Python and advanced prompt engineering frameworks
  • Experience with bias mitigation and statistical verification methodologies

Responsibilities

  • Architect and implement production ML infrastructure for large-scale models
  • Lead technical projects involving LangGraph for automated analytical tasks
  • Manage model lifecycles within isolated data sandboxes
  • Establish bias mitigation strategies and statistical verification gates
  • Mentor engineering team members for ongoing innovation and excellence

Benefits

  • Comprehensive benefits package
  • Hybrid work location in Arlington County, VA
  • Opportunity to lead AI innovation within a government context
  • Engagement with advanced technologies and complex enterprise environments
  • Work with the Department of War's authoritative data analytics platform
Full Job Description
Job Description

*AWAITING FINAL AWARD*

In this role, you will lead the design and implementation of production ML infrastructure, mentor technical talent, drive complex prompt engineering, and direct LangGraph multi-agent orchestration. You'll oversee automated Agent Test and Evaluation (T&E) harnesses while managing model lifecycles within isolated data sandboxes using MLflow.You will be building "enterprise capabilities" within the Department of War's authoritative data analytics platform (War Data Platform) for the Chief Digital and AI Officer (DoW CDAO). If you are passionate about leading AI innovation, establishing statistical verification gates, and pushing technology boundaries, we'd love to connect!

Key Responsibilities:

  • Architect and lead the implementation of infrastructure for training, validating, and deploying large-scale machine learning models into production.
    • Technical lead for advanced prompt engineering frameworks and multi-agent systems via LangGraph to support automated analytical tasks.
    • Oversee model lifecycles within isolated data sandboxes using MLflow, establishing enterprise bias mitigation and statistical verification gates.
    • Provide technical mentorship and guidance to engineering team members to ensure continuous innovation and technical excellence.


The annual base salary range for this role is $220,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Required Skills

Frameworks & Orchestration: Expertise in LangGraph multi-agent orchestration and building automated Agent Test and Evaluation (T&E) harnesses.

  • MLOps & Lifecycle Management: Hands-on experience with MLflow for tracking, managing model lifecycles, and managing isolated data sandboxes.
  • Advanced Machine Learning: Demonstrated proficiency in Python, Databricks Notebooks, and advanced prompt engineering frameworks.
  • Quality & Validation: Experience establishing bias mitigation, statistical verification gates, and deploying large-scale models into production.
  • Clearance: Active Top Secret, SCI Eligible
  • Experience: 10+ years of professional experience in machine learning, MLOps, or data science.
    • Education: Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
    • Work Location: Arlington County, VA (Hybrid)


Desired Skills

  • Collaborative leader with a drive for innovation and technical excellence.
  • Strong problem-solving abilities focused on continuous optimization and bias mitigation.
  • Passion for delivering impactful, reliable AI solutions across complex enterprise environments.

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