We are seeking a Software Engineer to join our Wearables AI team. This is a hybrid role combining language engineering expertise with systems generalist skills. You will focus on AI infrastructure and AI quality, designing and building robust, scalable LLM systems that power Agentic AI applications. Your work will span data generation and curation, tool design and implementation, infrastructure optimization, and building data and evaluation flywheels to drive rapid product improvements.
Responsibilities
Design, develop, and optimize AI infrastructure that supports LLM-powered wearable AI capabilities
• Build and maintain end-to-end machine learning pipelines, from data ingestion to model deployment, with a focus on agentic AI and tool use
• Drive AI quality initiatives including evaluation frameworks, data flywheels, and model performance monitoring
• Collaborate with ML researchers, product managers, and UX designers to translate technical solutions into production-ready features
• Develop robust APIs, services, and system architectures that enable reliable, low-latency AI experiences on wearable devices
• Monitor, debug, and iterate on deployed systems, ensuring reliability, performance, and security across the stack
• Contribute to technical documentation, design reviews, and cross-team knowledge sharing
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 5+ years of software engineering experience with expertise in building and scaling production systems
• Experience with systems design, distributed computing, or backend infrastructure
• Proficiency in one or more programming languages such as Python, C++, or Java
• Experience working with machine learning systems, LLMs, or AI infrastructure
Preferred Qualifications
• Knowledge of natural language processing, dialog systems, or agentic AI concepts
• Advanced degree (MS or PhD) in Computer Science or a related technical field
• Experience with deep learning frameworks (PyTorch, TensorFlow) and ML infrastructure
• Experience working on wearable or assistant AI technologies
• Experience debugging and optimizing performance across complex distributed systems
