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$ cat jobs/sr-applied-machine-learning-engineer-search-yurts-33b6f77f4512.json

Sr. Applied Machine Learning Engineer - Search

yurts·US·United States·senior
ml
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About Legion Let’s be real, AI isn’t magic; Legion was built to move beyond AI hype—delivering secure, reliable systems that work alongside the people tackling the world’s most critical challenges. Born from a Department of Defense partnership and trusted by leaders across government and enterprise, Legion embeds intelligence inside complex systems, unlocking data, accelerating human workflows, and strengthening mission-critical systems. We don’t replace workflows—we optimize them, ensuring quality, efficiency, and reliability inside the platforms our partners already use. With world-class collaborators like Palantir, Nvidia, HPE, and Oracle, we’re building intelligent infrastructure that enhances human capability and drives impact at the edge and across a range of enterprises. We’re looking for bold thinkers and doers to join us in shaping the future of AI that’s secure, grounded, and built to work. Staff Applied Machine Learning Engineer (Remote USA) ***US Citizenship or Greencard is required due to US Government contract requirements*** Job Summary: In this role, you will leverage your expertise in AI/ML engineering to design, develop, and deploy innovative machine learning and algorithmic solutions. If you are adept at building models that solve hard problems, we encourage you to apply. You will collaborate closely with platform engineers and product partners, bringing a strong product orientation to your ML work. 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 produc

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