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Wonderschool

Early Career Software Engineer (Applied AI)

Posted Updated
Discussion
  • We are seeking an Early Career Software Engineer with an interest in applied AI to join our growing team
  • This is a unique opportunity to work in a fast-paced, purpose-driven environment where you can apply your technical skills to create meaningful impact in the childcare ecosystem
  • You’ll collaborate with cross-functional teams to build scalable, AI-driven solutions that empower childcare providers and improve parent experiences
  • Design, develop, and maintain robust software solutions with a focus on integrating AI capabilities
  • Collaborate with product managers, designers, and engineers to define requirements and implement innovative features
  • Design and Development of AI Agents: Build modular, task-specific AI agents capable of natural language understanding, dialogue management, and action execution using frameworks such as LangChain or Rasa
  • Debug and troubleshoot technical issues to ensure platform stability
  • Stay current with emerging technologies and best practices in software engineering and AI
  • Familiarity with AI/ML concepts and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Strong foundation in programming languages (e.g., Python, JavaScript, or TypeScript)
  • Bachelor’s degree in Computer Science, Engineering, or related field
  • Basic understanding of cloud platforms like Google Cloud Platform and AWS
  • Excellent communication skills and ability to work in a collaborative, in-person environment
  • Strong understanding of machine learning principles, including model development, evaluation, and deployment for real-world applications
  • Retrieval-Augmented Generation (RAG) Pipelines: Design and deploy RAG pipelines by integrating retrievers with generative models to enable contextual, real-time responses using vectorized knowledge bases
  • Continuous Learning: Incorporate user feedback loops and data augmentation techniques to iteratively improve the performance and relevance of AI agents and RAG pipelines

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