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Sr. Applied Machine Learning Engineer - Search

San Francisco (Remote)

Company Overview:

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 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.

Job Summary:

As a Senior Applied ML Engineer - Search, you will be designing, implementing, and optimizing search capabilities for our enterprise-level AI platform. Your responsibilities will include measuring search performance, deploying efficient enterprise search solutions for various document types, and deeply leveraging LLMs and AI agents to enhance document enrichment, ranking, and retrieval techniques. Additionally, you will collaborate closely with our infrastructure and platform team to integrate search and ML techniques.

Responsibilities:

  • Design and build scalable enterprise search solutions, focusing on efficient indexing, retrieval.
  • Develop and maintain search ranking algorithms using machine learning, vector search, and LLMs to enhance search results and reduce latency.
  • Contribute to our large-scale machine learning codebase, leading the search-related components and ensuring code quality, scalability, and maintainability.
  • Apply your production experience with search platforms (e.g., Elasticsearch, Solr) and machine learning systems to ensure the scalability and reliability of our search infrastructure.
  • Stay updated with the latest advancements in search and ML technologies, vector search, and LLMs, and apply them to improve our applied machine learning search solutions.
  • Work with a collaborative team of other ML engineers building AI solutions.
  • Contribute to a culture of continuous learning.

Required Skills and Qualifications:

  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, or equivalent experience.
  • 3+ years of experience in ML and search
  • Familiarity with document enrichment techniques, with experience in leveraging LLMs and other machine learning models for improved enrichment.
  • Knowledge of search ranking algorithms, index optimizations, search query optimization, and experience applying machine learning to improve search relevance.
  • Excitement and enthusiasm for exploring and leveraging advanced search techniques
  • Growth mindset and low ego – you’re eager to pick up new tools and technologies, learn from others, and be open to changing course when it’s right.

Compensation Information

$205,000 - $260,000 USD

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