Senior Staff ML Engineer - Remote AI for Secure Systems

Mixpeek; San Francisco (CA); Remote; USD 200,000 - 240,000; Full time

Job summary

Legion is seeking a Staff Applied Machine Learning Engineer (Remote USA) to design, develop, and deploy innovative ML models and algorithms. You will work closely with platform engineers and product partners to translate bold ideas into production systems, delivering reliable AI solutions that meet real-world needs.

This role requires expert-level ML deployment experience, building scalable knowledge graphs, and strong collaboration across teams.

Qualifications

• US Citizenship or Greencard required for US Gov contract.
• 10+ years of ML engineering experience.
• Experience with knowledge graphs and semantic representations.
• Strong cross-functional collaboration and communication.
• PhD preferred but not required.

Responsibilities

• Lead ML model development for high-impact projects.
• Design and develop systems with knowledge graphs and entity detection.
• Own ML solutions end-to-end with product and platform teams.
• Assess runtime complexity and production costs of ML models.
• Communicate modeling decisions to technical and non-technical stakeholders.
• Build and maintain enterprise products with high quality and speed.
• Own projects from design to maintenance.
• Support production systems and debug distributed systems.
• Apply latest AI advances to drive innovation.

Skills

ML engineering

Knowledge graphs

Agentic AI

Communication

Production systems

Cross-functional collaboration

Learning mindset

Inclusion in discussions

Education

Bachelor’s or Master’s in CS/ML/NLP

Tools

Kubernetes

Job description

Legion is seeking a Staff Applied Machine Learning Engineer (Remote USA) to design, develop, and deploy innovative ML models and algorithms. You will work closely with platform engineers and product partners to translate bold ideas into production systems, delivering reliable AI solutions that meet real-world needs.

This role requires expert-level ML deployment experience, building scalable knowledge graphs, and strong collaboration across teams.