Machine Learning Engineer, Quality Analytics

<div class="content-intro"><p>Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.</p></div><p><span data-contrast="none">We are seeking a versatile and hands-on <strong>Machine Learning Engineer </strong>to join our Quality Analytics team. You will be a critical bridge between data science and engineering, responsible for the development of machine learning solutions that solve real-world manufacturing challenges. You will leverage your expertise in statistical analysis, general machine learning, and software engineering to build and deploy robust models for predictive quality, yield optimization, anomaly detection, and root cause analysis. You will work within existing business systems </span><span data-contrast="none">(ERP, MES, Inventory Management, Warehouse Management, Quality Incident management system and QMS systems)</span><span data-contrast="none"> to build, maintain, and improve the data analysis. Your work will directly contribute to improving product quality, reducing waste, and increasing operational efficiency on our factory floor. This role combines AIML model development with data pipeline development with deep-dive investigation into data quality as it relates to manufacturing quality. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335559740":240}"> </span></p> <p><strong><span data-contrast="none">WHAT YOU’LL DO</span></strong><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335559740":240}"> </span></p> <ul> <li data-leveltext="" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="text-start" data-ccp-parastyle-defn="{"ObjectId":"8196cb6b-cd51-5eab-845a-560d08e94671|1","ClassId":1073872969,"Properties":[201342446,"1",201342447,"5",201342448,"1",201342449,"1",469777841,"Times New Roman",469777842,"Times New Roman",469777843,"Times New Roman",469777844,"Times New Roman",201341986,"1",469769226,"Times New Roman",268442635,"24",469775450,"text-start",201340122,"2",134233614,"true",469778129,"text-start",335572020,"1",335559740,"240",201341983,"0",134233118,"true",134233117,"true",469778324,"Normal"]}">Design, build, deploy, and </span><span data-ccp-parastyle="text-start">maintain</span><span data-ccp-parastyle="text-start"> machine learning models to address key manufacturing problems, including classification (e.g., defect type), regression (e.g., yield prediction), and clustering (e.g., process regime identification).</span></span></li> <li data-leveltext="" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-ccp-parastyle="text-start">Perform in-depth exploratory data analysis (EDA) and statistical analysis on complex manufacturing datasets (sensor data, MES records, quality logs) to uncover insights and </span><span data-ccp-parastyle="text-start">validate</span><span data-ccp-parastyle="text-start"> hypotheses using Python, Pandas, Scikit-le ... (truncated, view full listing at source)