Associate Software Engineer (AI/Machine Learning)

Relay is transforming the physical world into a searchable, actionable data asset. We’ve moved beyond "Big Radio's" analog past to build the Relay SOAR™ Platform, which treats voice and movement as the new keyboards of the enterprise. By capturing the "Human Signal," we enable frontline teams in hospitality, manufacturing, and healthcare to move from reactive chaos to proactive control. Ranked among the fastest-growing tech companies in North America, we are looking for the next generation of "Relayers" to help us digitize the final frontier of the workforce. Why Start Your Career at Relay? Work at the Edge of Innovation: We just secured our 100th patent. You’ll work with technologies spanning AI-driven noise suppression, real-time language translation, and advanced IoT connectivity. Massive Scale: Be part of a platform that processes over 1 billion data points every week. Our tech isn't just "cool"—it’s essential infrastructure for the global economy. LIT Culture (Learning, Impact, Teamwork): We pride ourselves on an environment where early-career professionals have a seat at the table and see their work impact global brands immediately. Hyper-Growth Trajectory: With 461% growth and new C-suite leaders who have led successful IPOs, you are joining a rocket ship at the perfect time. Best-in-Class Perks: Based in our high-tech Raleigh headquarters, you’ll enjoy 100% compa [... source excerpt omitted ...] mble and lean teams, and you’ll make meaningful contributions to the product very quickly! There are lots of opportunities to learn new things, and we are constantly delivering to customers. Scale is a key focus for our team. As we see continued growth, team members are expected to think about and improve the scalability of all aspects of the product. You’ll focus on new product development of our communication platform. The platform consists of the following components, each with its own team. There are opportunities to move across teams. Responsibilities: Collaborate with cross-functional teams to identify business challenges and opportunities that can benefit from machine le [... source excerpt omitted ...] del parameters and hyperparameters to achieve optimal performance and generalization. Collaborate with the software engineering team to integrate machine learning models into the production environment. Ensure scalability, reliability, and efficiency of deployed models. Establish mechanisms for monitoring the performance of deployed models and identifying potential issues. Proactively maintain and update models as necessary to adapt to changing data and business requirements. Ensure compliance with data privacy regulations and implement security measures to protect sensitive information. Maintain comprehensive documentation of model development, methodologies, and results to fa