[Remote] Staff Applied Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Legion Intelligence builds secure, reliable AI systems that support critical government and enterprise workflows. The Staff Applied Machine Learning Engineer will design, develop, deploy, and maintain machine learning and algorithmic solutions, including knowledge graph, entity detection, and Agentic AI systems, while collaborating with product and platform teams and supporting production reliability.

Responsibilities

• Lead the development of machine learning models and data-driven algorithms for high impact projects
• Lead the design and development of complex systems involving knowledge graphs and advanced entity detection
• Collaborate with product and platform teams to own ML solutions end-to-end
• Understand the runtime complexity of algorithms and the cost to run ML models at a production scale
• Clearly communicate modeling decisions, tradeoffs, and limitations to technical and non-technical stakeholders
• Build, deliver, and maintain enterprise products, ensuring they meet high-quality standards while shipping fast
• Take ownership of your work, from design to implementation and maintenance, and drive projects to successful completion
• Support production systems, handling debugging challenges in distributed systems to ensure reliability and uptime
• Adapt quickly, bringing in latest developments in AI and machine learning, and proactively apply this knowledge to drive innovation within the company

Skills

• US Citizenship or Greencard is required due to US Government contract requirements
• Bachelor's or Master's degree in Computer Science, Machine Learning, NLP
• 10+ years of experience in ML engineering with a proven track record of building models for large-scale systems
• Experience building and supporting knowledge graph and semantic representation systems
• Proven experience designing, building, evaluating, and optimizing Agentic AI systems, including reasoning loops, tool use, orchestration patterns, context management
• Strong communication skills and the ability to collaborate effectively with cross-functional teams
• Comfortable supporting production systems and debugging challenges in distributed systems
• Demonstrated effectiveness in using AI tooling to accelerate research and development workflows
• Growth mindset and low ego- you're eager to pick up new tools and technologies, learn from others, and being open to changing course when it's right
• Drive to foster a culture of collaboration, psychological safety, and technical excellence
• Strong advocate for inclusion in technical discussions at all levels
• PhD is preferred
• Start-up experience or comfort in 0→1 product environments
• Familiarity with Kubernetes is a plus
• Experience integrating machine learning models and data driven algorithms into larger system architectures

Company Overview