L
Levente Szabo
About
Detail
Founder, Founder
New York, United States
Résumé
Jobs
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Lead Software EngineerServe RoboticsDec 2025 - Current (7 months)- AI EngineerServe RoboticsOct 2025 - Nov 2025 (2 months)
- Founder & AI EngineerJourneyman AIMay 2024 - Jul 2025 (1 year 3 months)Proven 0-to-1 product builder; independently conceived, developed, and launched 'DotBridge,' a multimodal platform for real-time conversational voice agents over video (WebRTC). Architected and deployed end-to-end ML systems on client AWS infrastructure, including a high-throughput job recommender serving sub-second responses. Designed and prototyped generative AI systems, including agentic RAG pipelines for complex knowledge retrieval, working across the full stack from Python/Flask to React. Managed all aspects of the venture, including product development, technical strategy, engineering execution, and client engagement
- Senior Manager, ML Engineering & Risk InfrastructureKatapultFeb 2023 - Apr 2024 (1 year 3 months)Led and mentored a cross-functional team of 3 ML Engineers and Data Scientists, responsible for hiring, career development, and performance management. Architected and led the development of a high-throughput, serverless underwriting engine on AWS (Step Functions, Lambda, Batch), processing 1m applications and ~$250m volume annually. Owned the P&L for risk-based pricing, leveraging deep domain expertise to develop and productionize a suite of credit risk models (Logistic Regression, XGBoost) that formed the core of the underwriting business. Engineered a comprehensive MLOps framework for automated backtesting and model validation using Python, S3, and SQL, significantly reducing pre-production risk and deployment cycle time. Served as t
- Senior Data ScientistKatapultDec 2021 - Feb 2023 (1 year 3 months)Shipped microservice APIs for real-time underwriting and pricing; integrated credit bureaus, identity verification, and fraud vendor data directly in ML models (Logistic Regression, XGBoost, KMeans). Led feature engineering efforts, creating novel behavioral, device, and identity-based features to significantly improve fraud detection and risk assessment. Built portfolio risk and loss forecasting workflows and designed A/B testing frameworks to optimize policy thresholds and models using scikit-learn and AWS SageMaker.
- Data ScientistKatapultMar 2021 - Dec 2021 (10 months)Contributed to the development of underwriting and decisioning microservices on AWS for point-of-sale credit solutions. Collaborated with cross-functional teams to integrate data-driven insights into lending product development.
- Data AnalystNovo NordiskJun 2020 - Aug 2020 (3 months)Built an NLP pipeline to identify principal investigators from unstructured trial artifacts; Python, Alteryx, SQL, scikit-learn.
- Data ScientistSmartfluenceMay 2019 - Sep 2019 (5 months)Applied LDA topic modeling to influencer/page content for campaign planning; Python/Jupyter, Pandas, Keras, scikit-learn.
- Research AssistantCornell UniversityJun 2017 - Aug 2017 (3 months)Worked on Mathematics research with Dr. Robert Strichartz focusing on Fractals and Differential Equations on Fractals.
Education
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- Master of Science - MS, Computer ScienceNew York UniversityJan 2019 - Dec 2021 (3 years)NYU Courant Institute of Mathematical Sciences
- Bachelor's degree, Mathematics and Computer ScienceUniversity of North Carolina AshevilleJan 2014 - Dec 2018 (5 years)
Projects (professional or personal)
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- SSystematic FX Alpha from State-Space Neural NetworksAug 2025Built a model that learns the “state” of the FX market from hourly data across seven major pairs. Instead of making one-point predictions, it forecasts the full distribution of returns at two horizons: one day ahead (24h) and one week ahead (168h). We only trade when the forecast looks strong relative to its own uncertainty (z-score gating), and we size our positions so risk stays balanced. The result is a USD-neutral portfolio that remains profitable out-of-sample, even after accounting for realistic trading costs. Sharpe 2.2 in sample and ~1.7 OOS.
- MMarket Manifolds: Geometry-Aware Latent Representations via β-VAEJun 2025 - Aug 2025 (3 months)Novel framework for discovering the intrinsic geometry of financial time series through β-variational autoencoders. By treating the VAE decoder as a parameterization of an embedded manifold, we compute Riemannian metric tensors and geodesic distances that respect the learned curvature of market states, enabling geometry-aware analysis and clustering.
- MMiami Beach Hotel Arbitrage — Alternative Data Alpha GenerationMay 2025 - Jun 2025 (2 months)Signal-driven acquisition and repositioning of a five-hotel, 356-key Miami Beach portfolio. We used alternative data to surface a quantifiable “crisis of competence” in 3–4 star assets and a management arbitrage among low‑touch operators. Modeled outcomes: 26.5% levered IRR and 2.85× equity multiple over five years
- DDotBridge - Multimodal AI for Video: Knowledge Graphs & Voice AgentsAug 2024 - Mar 2025 (8 months)Framework for systematic knowledge extraction from multimodal content (video, audio, text). It converts raw videos into temporally aligned transcripts and structured knowledge graphs, then orchestrates LLMs and real-time voice to enable interactive, conversational Q&A grounded in the source content.
- PPredicting Loan RepaymentMar 2021Analyze loans and borrowers in order to predict if a loan will be repaid or not. The data is analyzed, visualized and a binary classification model is tuned using XGboost giving approximately 92.3% accuracy on a test dataset.
- AAnalytics of r/WallStreetBetsJan 2021 - Feb 2021 (2 months)To gain insight on the evolving nature of the popular reddit forum r/WallStreetBets all forum comments were collected and analyzed to provide up to date statistics regarding forum activity over the previous week. The forum is known for having a large effect on several stocks during the beginning of 2021. This application was created to monitor potential changes in crowdsourced behavior regarding financial products. The system architecture displayed below is deployed using the Google Cloud Platform and features an ingestion, buffering, storage, visualization and deployment phase.
- CCOVID-19 ForecastingJan 2020 - Jun 2020 (6 months)Combined epidemiological SEIR models with a nearest neighbor heuristic to build a COVID-19 predictive model on 250,000 datapoints spread across over 3,000 U.S counties. Visualized predictions through a Tableau dashboard and deployed as a Flask web application on the Heroku platform.
- MMiniature DatabaseNov 2019 - Dec 2019 (2 months)Python implementation of a relational database which supports indexing on numerical data (using Hash or BTree). Support Select, Join, Groupby, Count, Sum, Average, Moving Sum and Moving Average functions.
- AActivity ClassificationSep 2019 - Dec 2019 (4 months)Keras implementation of an activity classifier, trained and tested on the EgoHands dataset (cards, chess, jenga, puzzles). Uses the bounding boxes of each hand (obtained as features or Mask-RCNN output) to construct a region of interest which is then fed through a multi layer 2D convolutional neural network.
- MMask RCNNSep 2019 - Dec 2019 (4 months)Pytorch implementation of a state of the art image segmentation algorithm, trained and tested on the EgoHands dataset. Uses a pre-trained torchvision model with a resnet-50 backbone and trained with a gpu using an HPC system. Outputs a segmented video file.
- AAdvertising AnalyticsAdvertising Analytics To understand the performance of a variety of advertisment groups we first calculate performance metrics, then we attempt to forecast the number of adds shown 3 weeks ahead. Finally we calculate the percent change in cost per click and cluster the ad groups accordingly.
Awards
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- NGraduate Merit AwardNorth Carolina State UniveristyJun 2018An award of $8000 for the first year of graduate study
- UMagna Cum LaudeUNC AshevilleMay 2018
- ACM Programming Competition: 2nd at Chapel Hill SiteACM ICPCNov 2016The ACM ICPC is an international programming competition for undergraduate students. My team from UNC Asheville placed in 2nd place at the local site of the southeast regional competition.
Publications
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- AUnimodality of the independence polynomials of non-regular caterpillarsAustralasian Journal of CombinatoricsMar 2018The independence polynomial of a graph G is the polynomial in variable x whose coefficients give the number of independent subsets of vertices of G. While the independence polynomials of many families of graphs with highly regular structure is known to be unimodal little is known about less regularly structured graphs. We analyze the independence polynomials of a large infinite family of trees without regular structure and show that these polynomials are unimodal through combinatorial analysis.
- tAnalysis on the Projective Octagasketth Cornell Fractals Conference ProceedingsJan 2018The existence of a self similar Laplacian on the Projective Octagasket, a non-finitely ramified fractal is only conjectured. We present experimental results using a cell approximation technique originally given by Kusuoka and Zhou. A rigorous recursive algorithm for the discrete Laplacian is given. Further, the spectrum and eigenfunctions of the Laplacian together with its symmetries are categorized and utilized in the construction of solutions to the heat equation.