Staff Applied Machine Learning Engineer (Remote - Anywhere in USA)

<p><strong>About us:</strong></p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p><strong>Job Summary:</strong></p> <p>Are you an experienced Applied Machine Learning Engineer who thrives in a fast-paced, collaborative team? We seek a highly skilled Senior Applied Machine Learning Engineer to join our Applied ML team. In this role, you will leverage your expertise in AI/ML engineering to design, develop, and deploy innovative machine learning and algorithmic solutions.&nbsp;</p> <p>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.</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Lead the development of machine learning models and data-driven algorithms for high impact projects</li> <li>Collaborate with product and platform teams to own ML solutions end-to-end</li> <li>Understand the runtime complexity of algorithms and the cost to run ML models at a production scale</li> <li>Clearly communicate modeling decisions, tradeoffs, and limitations to technical and non-technical stakeholders</li> <li>Build, deliver, and maintain enterprise products, ensuring they meet high-quality standards while shipping fast</li> <li>Take ownership of your work, from design to implementation and maintenance, and drive projects to successful completion</li> <li>Support production systems, handling debugging challenges in distributed systems to ensure reliability and uptime</li> <li>Adapt quickly, bringing in latest developments in AI and machine learning, and proactively apply this knowledge to drive innovation within the company</li> </ul> <p><strong>Required Skills and Qualifications:</strong></p> <ul> <li>Bachelor’s or Master’s degree in Computer Science, Machine Learning, NLP</li> <li>Minimum 5+ years of experience in applied machine learning, with a track record of delivering enterprise products</li> <li>Proven experience in Generative AI, including fine-tuning, optimizing, and evaluating LLMs, RAG pipelines, and Agentic AI systems</li> <li>Strong proficiency with AI/ML/NLP techniques, resources and methodologies (ex: Huggingface, Spacy, Scikit-learn, Pytorch).</li> <li>Strong communication skills and the ability to collaborate effectively with cross-functional teams</li> <li>Comfortable supporting production systems and debugging challenges in distributed systems</li> <li>Demonstrated effectiveness in using AI tooling to accelerate research and development workflows</li> <li>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</li> </ul> <p><strong>Preferred Qualifications:</strong></p> <ul> <li>Start-up experience or comfort in 0→1 product environments.</li> <li>Familiarity with Kubernetes is a plus.</li> <li>Experience integrating machine learning models and data driven algorithms into larger system architectures.</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="title">Compensation Information</div><div class="pay-range"><span>$205,000</span><span class="divider">&mdash;</span><span>$260,000 USD</span></div></div></div>