# David Tagliamonti > Sr. Staff Software Engineer at Ambient.ai Location: San Francisco Bay Area, United States Profile: https://flows.cv/davidtagliamonti I’m currently a Senior Staff Software Engineer on the Platform team at Ambient.ai [a16z, Series B, 72M raised], broadly working across all our backend services, with a focus on our Machine Learning Infrastructure, Data Streaming and Processing pipelines, and Edge Computing systems. I’m also the product lead for Forensics, an AI-powered video search tool. I previously held roles as an Applied Research Scientist and later Senior Research Scientist in our Machine Perception team, where I worked on applying the latest advances in Deep Learning and Computer Vision to our Perception platform, and gradually shifted from an ML focus to a more traditional SWE role. I joined Ambient.ai as employee no. 15. In June 2019, I graduated from Stanford University with a Master’s in Computer Science. During my Master’s, I specialized in Artificial Intelligence - more specifically, Deep Learning - and built a broad foundation in Computer Science and Systems. I was involved in academic research during much of my time at Stanford and held the Siebel Scholar Fellowship. Prior to that, I completed a Bachelor’s in Actuarial Mathematics – a field at the intersection of mathematics, statistics, and finance – and received the Governor General of Canada’s Academic Medal for ranking first in my graduating class, among 4,000+ students in all disciplines. Over the course of my undergrad, I completed 22 months of internships in the insurance (Life and P&C), consulting, and pharmaceutical industries, was part of the winning team for the largest national actuarial case competition (Munich Re Cup), and passed the first 5 professional exams of the Society of Actuaries. ## Work Experience ### Senior Staff Software Engineer @ Ambient.ai Jan 2025 – Present | San Francisco Bay Area ### Staff Software Engineer @ Ambient.ai Jan 2022 – Jan 2025 | San Francisco Bay Area ### Senior Research Scientist @ Ambient.ai Jan 2020 – Jan 2022 | San Francisco Bay Area ### Applied Research Scientist @ Ambient.ai Jan 2019 – Jan 2020 | San Francisco Bay Area ### Research Assistant @ Stanford University Jan 2018 – Jan 2019 | San Francisco Bay Area I worked with Prof. Stefano Ermon and one of his PhD students on theoretical and applied projects, namely: • Designing and implementing a Reinforcement Learning (RL) -based SAT solver in Python • Implementing a novel approach to using deep generative models of environment dynamics in RL applications in TensorFlow ### Data Science Intern @ Hopper Jan 2018 – Jan 2018 | Montreal, Canada Area • Designed and implemented a recommendation engine to propose travel destinations to app users • Studied the effect of app layout on sales conversion, revealing novel insights that led to changes in the app design ### Actuarial Intern, Capital and Strategic Planning @ TD Insurance Jan 2017 – Jan 2017 | Montreal, Canada Area • Developed an extensive library of efficient SAS code to prepare data for modelling • Developed a reusable predictive modelling framework in R to forecast business volumes • Wrote documentation to support the continued production use of the predictive model ### Actuarial Co-op, DB Solutions, Pricing @ Sun Life Financial Jan 2016 – Jan 2016 | Toronto, Canada Area • Worked within the Defined Benefit (DB) Solutions team, which offers products and services to help de-risk pension plans • Assisted in the pricing of multi-million dollar group annuity contracts sold to pension plans ### Actuarial Intern, Professional Services @ Aon Risk Solutions Jan 2015 – Jan 2015 | Montreal, Canada Area • Worked within the actuarial consulting team, providing solutions for captives insuring accountants’ professional liability (errors & omissions) • Worked with, and made updates to, simulation-based (frequency/severity) loss forecasting models • Presented the results of these models; assisted in the review of the resulting funding report delivered to the client • Performed a technical review of a capital model and proposed improvements • Performed other ad-hoc work, including a statistical study to review claims inflation assumptions ### Actuarial Intern, General Insurance, Product Management @ TD Insurance Jan 2015 – Jan 2015 | Montreal, Canada Area • Performed ad-hoc data analysis and optimization using SAS, Excel, and Access • Proposed and executed Monte Carlo simulation techniques as part of a project business proposal • Wrote an Excel VBA application with a user interface to automate reporting of marketing data ### Intern, Market Access @ Pharmascience Jan 2014 – Jan 2014 | Montreal, Canada Area • Developed a customized database application to track upcoming product launches and streamline workflow during the product launch process • Wrote a user guide and conducted training sessions to train users and the administrator of the database application • Worked with a team of fellow interns to research contributing factors leading to current slow-moving inventory • Presented findings of inventory project to an audience of 100+ participants ## Education ### Master of Science (MS) in Computer Science Stanford University ### Bachelor of Science (BSc) in Actuarial Mathematics Concordia University ## Contact & Social - LinkedIn: https://linkedin.com/in/davidtag --- Source: https://flows.cv/davidtagliamonti JSON Resume: https://flows.cv/davidtagliamonti/resume.json Last updated: 2026-04-01