Accountabilities

• Build and improve machine learning models that power interactive AI roleplay and coaching experiences.
• Develop systems that can listen to and interpret learner responses during roleplay sessions and assess their performance.
• Create real-time feedback capabilities that provide learners with useful, actionable guidance on their communication and performance.
• Develop AI-driven decision-making systems that determine how virtual avatars should respond based on learner behavior and conversation context.
• Apply machine learning expertise to solve practical product challenges and translate technical capabilities into valuable user experiences.
• Contribute to different product initiatives as a product-focused software engineer, balancing ML development with broader software engineering responsibilities.
• Work collaboratively within a high-performing engineering team to design, build, test, and iterate on scalable product solutions.
• Prioritize pragmatic execution, rapid experimentation, and measurable commercial and product outcomes.
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Requirements

• At least seven years of professional software engineering experience, including at least two years working at a senior level.
• Strong practical knowledge of machine learning and the ability to apply ML concepts to real-world product challenges rather than focusing primarily on academic research.
• Demonstrated experience working within a high-performing engineering organization operating at scale, whether in a scale-up or an established company with a strong engineering culture.
• Strong product and commercial orientation, with an understanding of how technical decisions and product improvements contribute to business success.
• Strong software development skills and the ability to operate as a product-focused engineer across different types of product work.
• A pragmatic, action-oriented approach with a willingness to iterate quickly, experiment, and adapt solutions based on results.
• Strong collaboration and communication skills, with the ability to work effectively in a fast-moving, multidisciplinary engineering environment.
• A demonstrated ability to take ownership, solve complex problems, and deliver meaningful outcomes with a high degree of autonomy.