• Build foundational new features such as implementing translation capabilities powered by LLMs • Improve LLM model results using techniques like vector search • Develop LLM Infrastructure and design evaluation and logging systems • Engage with customers to understand their needs and improve product • Collaborate across various roles including coding and user research • Shape the team culture by encouraging initiative and product quality

• Building high-quality software for our voice AI platform, from rapid prototypes that push the boundaries of what's possible to production-ready, scalable solutions • Continuously improving our AI capabilities and accuracy through experimentation, data analysis, and innovative approaches • Implementing and optimizing LLM and voice technology while balancing intelligence, latency, and cost • Collaborating across engineering and cross-functional teams to tackle challenging technical problems throughout the full lifecycle of our voice AI products - from ideation and prototyping to deployment and monitoring • Develop voice-specific product features from the ground up, such as implementing voice recognition capabilities powered by LLMs and intelligent categorization of incoming calls. You'll help design and build intuitive interfaces for support agents to monitor and interact with AI voice assistants. • Enhance our voice recognition and generation engine using advanced techniques. You'll help us leverage implicit knowledge bases to improve model performance in voice contexts. • Architect the abstractions that enable integration of various types of LLMs tailored for voice applications. You'll design and implement evaluation and logging systems to monitor performance. • Collaborate with our customers (both support agents and managers) to understand how they interact with our voice product, and how we can improve their experience. • Be versatile in roles — coding, user research, planning, brainstorming, and cross-team collaboration. • Encourage a startup mentality focused on product quality and taking initiative.

• Collaborate with a team that delivers features to support dataset curation, model analysis, and integrations that span the entire machine learning lifecycle. • Build clean, scalable APIs and solve unique challenges that arise when working with unstructured data (images and video). • Contribute to a thriving open source community while also emphasizing enterprise-grade engineering for our commercial products. • Develop our open source SDK, as well as our enterprise APIs, UIs, and backend systems. • Help us scale our enterprise solution to support the largest vision AI datasets in existence, supporting individual researchers to Fortune 500 companies; processing petabytes of data. • Write production code that is maintainable, flexible, performant, and well tested. • Contribute to the department through tooling, automation, and best practices.

• Improve our existing VTK-based rendering pipeline • Investigate alternative foundational libraries to potentially move to • Work with our applications engineers to understand and fix key display bottlenecks.