Job Description

We’re building the next generation of AI-powered customer success. Our platform ingests and interprets real-time product usage data, conversational history (emails, chats, meetings), and other customer signals to proactively drive customer engagement, reduce churn, and increase satisfaction. If you’re excited about solving complex AI challenges with real-world impact and working at the intersection of machine learning, generative AI, and applied data science—this is the role for you. What You'll Do Lead the design and development of AI systems that analyze product usage and conversational data to generate intelligent, real-time customer insights. Research and prototype machine learning and generative AI models for: Customer intent prediction Churn and risk modelling Conversational summarization and generation Behaviour driven engagement automation Collaborate closely with engineering, product, and data teams to deploy AI models into production pipelines. Contribute to model evaluation, bias mitigation, and continuous improvement strategies. Stay current with AI/ML research and suggest applicable innovations to keep our product ahead of the curve. What We're Looking For Experience: 4+ years in AI/ML research or applied roles, ideally in a SaaS or customer-centric product environment. Expertise in: Natural Language Processing (NLP) and Conversational AI (e.g., summarization, dialogue generation) Machine Learning for time-series, behavioral analytics, and customer modeling GenAI frameworks (OpenAI, Hugging Face, LangChain, or similar) Strong understanding of data pipelines, feature engineering, and model evaluation. Experience working with large-scale unstructured and structured data. Demonstrated ability to convert research into deployable, scalable solutions. M.S. or Ph.D. in Computer Science, AI, Data Science, or a related field. Good to have: Experience with real-time data systems or event-driven architectures (e.g., Kafka, Pub/Sub). Prior work in Customer Success tech, CRM systems, or marketing automation platforms. Contributions to open-source AI/ML projects or published research papers. Show more Show less