Principal ML Engineer – eCommerce & Personalization Job at Autodesk, Inc. in San

This role can be remote within the U.S. or Canada, though San Francisco is the preferred location About the Team At GET (Growth Experience Technology), we’re transforming how customers discover, buy, and use Autodesk. Our mission is to build seamless, data-informed digital experiences that are intuitive, personalized, and scalable—empowering both our customers and internal teams. We’re investing in smarter platforms, connected sales and marketing systems, and technologies that unlock deeper customer insights and faster decision-making. The Role We’re looking for a Principal (Staff) Machine Learning Engineer to help shape the future of Autodesk’s B2C eCommerce platform. This role involves full-lifecycle ownership—from ideation and modeling to deployment and optimization. You’ll collaborate across disciplines to develop intelligent systems that personalize user experiences and deliver measurable impact. If you’re passionate about solving ambiguous business problems and building scalable ML systems—even if you don’t meet every qualification—we encourage you to apply. What You’ll Do Guide the design, training, and deployment of ML models for real-time personalization across Autodesk’s eCommerce ecosystem. Collaborate with Product Managers and Experience Designers to define what and how personalization should be implemented. Translate business pain points into scalable ML or analytics solutions. Work closely with the MLOps team to productionize models and ensure real-time inference performance. Develop experimentation frameworks and run A/B tests to measure impact (e.g., CTR, bounce rate, add-to-cart rate).Build models that scale across product categories, including third-party integrations for Autodesk’s evolving marketplace. Promote a data-informed culture by contributing to initiatives in segmentation, recommendation systems, forecasting, churn prediction, and product analytics. Mentor and support team members, fostering a collaborative and inclusive environment. Qualifications We recognize that talent comes in many forms. If you meet most of the criteria and are excited about the role, we’d love to hear from you. Preferred Experience Background in Data Science, Statistics, Computer Science, or a related field (we also welcome applicants from non-traditional DS backgrounds) 7+ years of hands-on related experience. We value experience with machine learning infrastructure, model deployment, optimization and with software design, architecture, and product development. Knowledge of data mining, information retrieval, and statistical modeling. Exposure to A/B testing and experimental design. Experience applying statistical and probabilistic methods to solve real-world problems; familiarity with financial modeling is a plus. Ability to connect data insights to business outcomes. Experience in eCommerce, marketing technology, go-to-market systems, or other high-scale data environments (e.g., fintech, social platforms). Bonus Experience (Not Required) Advanced degree preferred but not required. Equivalent industry experience is highly valued. Familiarity with cloud ML platforms (AWS, Azure) and MLOps practices. Experience with personalization systems and real-time inference pipelines. Work on high-impact projects that shape the future of digital commerce. Collaborate with a diverse and talented team of engineers, scientists, and product leaders.
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In Summary: We're looking for a Principal (Staff) Machine Learning Engineer to help shape the future of Autodesk’s eCommerce platform . This role involves full-lifecycle ownership—from ideation and modeling to deployment and optimization . The role can be remote within the U.S. or Canada, though San Francisco is the preferred location .

En Español: Esta función puede ser remota dentro de los Estados Unidos o Canadá, aunque San Francisco es la ubicación preferida acerca del equipo en GET (Team At Growth Experience Technology), estamos transformando cómo los clientes descubren, compran y usan Autodesk. Nuestra misión es construir experiencias digitales sin interrupciones e informadas sobre datos que sean intuitivas, personalizadas y escalables empoderando tanto a nuestros clientes como a equipos internos. Estamos invirtiendo en plataformas más inteligentes, sistemas de ventas y marketing conectados y tecnologías que desbloqueen conocimientos de clientes más profundos y toma de decisiones más rápidas. La función buscamos un ingeniero de aprendizaje automático principal para ayudar a dar forma al futuro de la plataforma de comercio electrónico B2C de AutoDesk. Trabajar estrechamente con el equipo de MLOps para producir modelos y garantizar el rendimiento de la inferencia en tiempo real. Desarrollar marcos de experimentación e ejecutar pruebas A/B para medir el impacto (por ejemplo, CTR, tasa de rebote, tasa añadida a cartón).Construir modelos que escalaran entre las categorías de productos, incluidas integraciones de terceros para Autodesk s mercado en evolución. Promover una cultura informada de datos contribuyendo a iniciativas en segmentación, sistemas de recomendación, pronóstico, predicción de tornos y análisis del producto. Mentor y miembros del equipo de soporte, fomentando un entorno colaborativo e inclusivo. Calificaciones Reconocemos que los talentos vienen en muchas formas. Si cumples con la mayoría de los criterios y estás entusiasmado con el papel, nos encantaría escucharte. Experiencias preferentes en ciencia familiar, estadística, computadora o un campo de recuperación de datos (también damos bienvenidos a los solicitantes de diseño de datos no tradicionales) Diseñar experiencia profesional y desarrollos de conocimientos técnicos relacionados con la arquitectura de máquinas, así como solucionar problemas asociados al desarrollo de información y la creación de tecnologías tecnológicas. Experiencia en el comercio electrónico, la tecnología de marketing, los sistemas de entrada al mercado u otros entornos de datos a gran escala (por ejemplo, fintech, plataformas sociales). La experiencia del bono (no requerida) grado avanzado es preferible pero no se requiere.