Daniel Weber

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• Led a 3-person team in developing one of the first immersive content sharing platforms for Apple Vision Pro. • Architected an AWS cloud solution utilizing Lambda, S3, and Cloudfront to provide HTTP Live Streaming (HLS) for spatial video content, reducing loading and buffering times by over 90%. • Spearheaded user outreach and conducted 50+ user interviews, which led to multiple new operational and strategic initiatives that more than doubled user engagement. • Conceptualized and developed a new immersive content creation method which combined 3D models, immersive video, and dynamic environments to unlock wholly new user experiences. • Proposed and developed novel AI methods for dynamic scene reconstruction based on NeRF and Gaussian Splatting reducing content creation time and cost by 99%. • Led company's strategic pivot from B2C to B2B, securing our first partnership with a major Hollywood production studio to use our novel AI technology.

• Architected and launched an LLM-powered application platform enabling no-code app creation, scaling to a 1,000+ user-generated applications within 7 days of launch • Engineered high-performance semantic search engine using a pgvector DB, allowing users to query across 100,000+ emails and 5+ inboxes in under a second • Developed executive assistant platform powered by AI agents that automated email management and follow-ups for clients, reducing administrative workload by over 5 hours/week • Partnered with C-suite to define product roadmap and GTM strategy, leading to identification of key market segments with $50M+ annual revenue potential

• Architected and maintained critical access control integrations with Azure and AWS, managing security permissions for 3,000+ enterprise employees while enabling security teams to quarantine suspicious accounts within seconds of detection • Led development of automated access review platform that reduced customer audit times by 90%, saving enterprise clients an average of 200 hours per quarter and increasing compliance accuracy to 99.9% • Supported 24/7 security incident response for enterprise clients, achieving a 100% resolution rate with zero data breaches and average response time under 8 minutes • Led 2-month strategic wind-down of our SaaS platform while maintaining 99.9% uptime for enterprise customers, orchestrating data migration for our clients, and achieving 100% contractual obligations

• Proposed an initiative to scale event publishing infrastructure via sharding to achieve an over 10X increase in throughput. • Autoscaled Kubernetes deployments using Datadog metrics to reliably ensure event processing within minutes of publishing. • Proposed and implemented a Google Pub/Sub publishing interface that allows developers to asynchronously publish events while maintaining ordering and data consistency. • Collaborated with developers both on and off-team to push cross-functional goals which improved organizational efficiency and the user-facing experience. • Increased the observability of our publishing systems by designing and integrating effective traces/metrics which allowed myself and peer developers to identify problems thus sparking new engineering initiatives.

• Designed and implemented a heap dump analysis tool to aid developers in the optimization of processes utilizing over 250GB of heap memory. • Collaborated with key stakeholders on the ad infastructure team to find the pain points in the existing optimization process. • Implemented automation to give developers easy access to up-to-date heap dump files, shortening an 8 hour process to a minutes long task. • Leveraged continuous development/integration to develop an extensible and resilient platform that can evolve with changing business needs.

• Created a transformer-powered NLU chatbot to replace an off-the-shelf rule-based Google Dialogflow model that dramatically improved customer workflows through context-aware responses and actions. • Curated large datasets to be used in the prediction of flight delays using web scraping. • Integrated with travel industry APIs to predict flight delays and proactively notify customers.

• Curated an extensive dataset of electricity usage predictors from both internal and external sources. • Developed machine learning models to predict a building’s electricity demand with 97% accuracy and deployed said models to allow for real-time prediction and scalability. • Architected an AWS cloud solution to allow the company’s resources to scale with demand.

• Utilizing flow cytometry to identify unique biomarkers on immune cells which will assist in the diagnosis and treatment of glioblastomas and other brain cancers. • Developing a method to more efficiently isolate cells from rare cell populations on slides for morphological analysis. Useful for diagnosis of B cell lymphomas through analysis of cells found in CSF.