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Zendesk is transforming customer experience and employee services with a unified Resolution Platform powered by AI, data, and cloud technologies to help brands deliver smarter, faster, and more personal service at scale. As a Sales Engineer, you’ll partner with customers and teams to design and showcase AI-driven solutions that address real-world challenges and unlock lasting value. You will lead technical and business discovery, run AI readiness assessments, and translate AI/ML capabilities into clear, business-focused narratives for audiences from IT to the C-suite. You’ll own the end-to-end technical engagement, architect secure, scalable solutions using Zendesk APIs, middleware, telephony, and cloud platforms, and measure impact with analytics to demonstrate ROI and drive AI adoption. Requirements include 5+ years of presales or solutions consulting in SaaS/CX or enterprise software, deep AI knowledge and domain expertise, strong communication and storytelling skills, a bachelor’s degree (graduate degree a plus), willingness to travel, and Zendesk’s hybrid, inclusive culture with equal opportunity and accommodations.

Zendesk aims to improve Customer Experience for 125,000+ brands by building AI-powered automation to help support teams handle more complex problems. The Senior Machine Learning Scientist will develop, evaluate, and deploy state-of-the-art NLP/ML models to power intelligent automation and customer service solutions at scale, collaborating with engineers, product managers, and cross-functional teams to impact millions of interactions. Daily work includes researching and prototyping models for intents, auto-assist, chatbots, and routing; designing rigorous offline/online experiments; productionizing ML solutions with data pipelines and monitoring; analyzing large multilingual datasets; and mentoring junior scientists. Key challenges involve multilingual language detection, sentiment analysis, scalable real-time routing, large-scale A/B testing, and exploring advanced techniques like retrieval-augmented generation while ensuring production model health and continuous learning. Qualifications include an MSc (PhD preferred) in a related field, deep ML/NLP knowledge, strong Python (PyTorch) skills, experience with large-scale experimentation, and the ability to collaborate; the tech stack includes AWS, PyTorch, Kubernetes/Docker, Kafka, and data services such as S3, RDS, Redis, ElasticSearch, Snowflake, and Aurora, with Zendesk emphasizing inclusive, hybrid work and accommodations for applicants.