<div class="content-intro"><p><a href="https://himalayas.app/companies/mixmode">MixMode</a> is a leading provider of AI-powered cybersecurity solutions at scale, pioneering a patented third-wave, context-aware AI approach that automatically learns and adapts to dynamic environments. The <a href="https://himalayas.app/companies/mixmode">MixMode</a> platform delivers self-supervised, real-time threat detection for known and unknown threats across cloud, hybrid, and on-premises environments. Large organizations with big data workloads – including those in enterprise, critical infrastructure, US Department of War and US Intelligence Community – trust <a href="https://himalayas.app/companies/mixmode">MixMode</a> to defend their most important assets. Backed by PSG and Entrada Ventures, <a href="https://himalayas.app/companies/mixmode">MixMode</a> is headquartered in Santa Barbara, California. Learn more at <a href="http://www.mixmode.ai/" data-saferedirecturl="https://www.google.com/url?q=http://www.mixmode.ai&amp;source=gmail&amp;ust=1728083199754000&amp;usg=AOvVaw3yjuh5o4eKDAcQPxQYJj7H" rel="nofollow ugc noopener noreferrer" target="_blank">www.mixmode.ai</a>.</p></div><p><a href="https://himalayas.app/companies/mixmode">MixMode</a> is looking for a Sr. Machine Learning Engineer to aid in building large-scale, production-grade AI systems for cybersecurity. As a Senior Machine Learning Engineer, you will design, build, and operate distributed systems that apply machine learning to petabyte-scale streaming data. This role combines machine learning with systems engineering. You will be responsible for ensuring that ML systems are reliable, scalable, and performant in production, while enabling fast, reproducible evaluation of model performance. You will work closely with researchers and engineers to bring models into production and continuously improve their behavior at scale.</p><h3>What you’ll be doing (responsibilities):</h3><ul><li>Design and operate production ML systems for large-scale, streaming data</li><li>Own system reliability, performance, and observability in production environments</li><li>Improve the speed and reproducibility of model evaluation and iteration</li><li>Collaborate with researchers to productionize models and integrate them into distributed systems</li><li>Contribute to the evolution of existing ML systems and infrastructure to improve scalability, maintainability, and performance</li></ul><h3>What you’ll need to bring (qualifications):</h3><ul><li>Ability to travel to our office in Santa Barbara, CA, a few times per year</li><li>5+ years of experience with Python in production environments</li><li>5+ years of experience applying machine learning using libraries such as PyTorch, scikit-learn, pandas, etc.</li><li>Experience building and operating distributed systems in production (e.g., Kubernetes, microservices, streaming systems)</li><li>Experience improving systems for ML experimentation and evaluation</li><li>Experience