Sr. Applied Machine Learning Engineer - Search

Legion is focused on delivering secure, reliable AI systems that optimize workflows and strengthen mission-critical systems, with collaborations across government and enterprise sectors.

Location: Remote (US)

Salary: $205,000—$260,000 USD

Responsibilities

• Lead the development of machine learning models and data-driven algorithms for high impact projects
• 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

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, NLP
• Minimum 5+ years of experience in applied machine learning, with a track record of delivering enterprise products
• Proven experience in Generative AI, including fine-tuning, optimizing, and evaluating LLMs, RAG pipelines, and Agentic AI systems
• Strong proficiency with AI/ML/NLP techniques, resources and methodologies (ex: Huggingface, Spacy, Scikit-learn, Pytorch)
• 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