Digital &Technology Software Engineering Internship
Pubblicato il 13-08-2026 - Altro in Italia
SurveyMonkey is the world's most popular platform for surveys and forms, built for business—loved by users. We combine powerful capabilities with intuitive design, serving every use case from customer experience to employee engagement, market research, and payment & registration forms. Built with research expertise and AI-powered technology, we help teams gather insights that inspire better decisions and drive business growth. What We're Looking For The Machine Learning Platform team (MLP) is seeking a Senior Software Engineer II to design and implement secure, highly scalable, and high-performance pipelines that govern the end-to-end lifecycle of ML models. You will work at the intersection of Data Science and DevOps, building the connective tissue that empowers our product portfolio to leverage technologies like Generative AI, Natural Language Processing (NLP), and real-time classification. You will report to the Senior Engineering Manager on the MLP Solutions team. What You'll Be Working On Build and maintain robust ML systems using Python (Pandas/NumPy, PyTorch/transformers)
to support efficient ML operations. Design ML cloud infrastructure using AWS services, ensuring the platform is built for reuse, scalability, and high-volume throughput. Collaborate with application engineers to integrate, test, and monitor ML model services across SurveyMonkey's microservices architecture. Act as a consultant to internal feature teams, educating and influencing decisions regarding ML tooling and infrastructure. Incorporate telemetry into the platform for complex failure mode analysis, ensuring real-time reliability for millions of daily survey responses. Serve as a technical leader and mentor, championing high standards in coding, documentation, and architectural best practices to foster the professional growth of junior engineers on the MLP team. Qualifications 8+ years of professional ML development experience with a proven track record of designing and implementing ML in