About Laszlo
I'm an AI Engineer building AI search and RAG systems that deliver mathematically proven outcomes.
I don't rely on "vibes" by eyeballing before-and-after results. Instead, I conduct statistically rigorous evaluation (using confidence intervals and paired significance tests) to ensure that any reported improvement is real not just noise.
I measure whether systems actually work before you invest engineering hours into them.
BACKGROUND:
Over 19 years in software engineering, from Nasdaq-listed firms to fast-paced startups, I have specialized in the full AI retrieval stack: hybrid search (BM25 + semantic), custom embeddings, cross-encoder reranking, fusion, GraphRAG, and knowledge graph retrieval.
AUTHOR & AUTHORITY:
- Author of "Designing Hybrid Search Systems" (Leanpub) - A practitioner's guide to BM25, dense retrieval, reranking, and fusion.
- Upcoming book: "Measuring Search: Quantifying Uncertainty for Confident Decisions" – Covering the measurement and statistics side of AI search.
WHAT CAN I DO FOR YOU:
- Independent evaluation: Auditing and evaluating your existing AI, retrieval, or RAG pipelines to identify precise bottlenecks and quantify ROI.
- Hands-on implementation: Architecting, building, or fixing complex search and AI systems from the ground up.
English
Fluent
Remote only
Primarily works remotely
Experience
- Syrup TechSenior ML EngineerTECHMay 2023 - Today (3 years and 3 months)Syrup’s ML-powered recommendation engine helps brands sell more while minimizing excess inventory.
- Replaced PostgreSQL with Snowflake as the primary data warehouse that enables processing 10x as much customer data as before
- Introduced enhanced demand forecasting with conformal prediction to quantify uncertainty, which enabled more accurate inventory allocation decisions and improved their acceptance rate by customers by 23%
- Developed a warehouse configuration tool to allow customers to define pattern-based product/store eligibility rules
Tech: Python, Prefect, DBT, Snowflake, MLFlow, XGBoost, AWS - UpworkStaff Software EngineerTECHMarch 2021 - April 2023 (2 years and 2 months)Owned the operational intelligence area's roadmap focused on getting data from different places, processing/aggregating it, deriving new data sets, and designing APIs to share insights.
- Designed an Engineering Data Platform that supports 657 engineers in making data-driven decisions.
- Led a team of 3 engineers to gradually discontinue legacy data processing applications with a unified pipeline model. The team has created 25 data pipelines and dashboards for use cases, such as finding metadata about 872 microservices, gaining insight into developer productivity, SLO tracking, resource usage forecasting, capacity planning, and anomaly detection.
- On-boarded 3 cross-functional teams and mentored their engineers on how to create their data pipelines.
Tech: Java, Python, Dagster, Numpy, Scipy, Statsmodels, AWS Athena, AWS Aurora, AWS Kinesis - UpworkSenior Software EngineerTECHJanuary 2020 - February 2021 (1 year and 2 months)Upwork is a global freelance marketplace where businesses and independent professionals connect and collaborate remotely.
- Designed a framework for automating manual DevOps procedures and automated the 5 most tedious tasks engineers had to file tickets for before. The team I led then created 28 new automations using this framework. These automations were triggered 19K times at the time of writing, saving thousands of man-hours.
Tech: Microservices, Java, DropWizard, AWS ECS- Designed an automated root cause analysis tool to help SREs resolve customer-facing incidents faster. The tool points out directly which Kubernetes pods are misbehaving out of the 872 microservices making up upwork.com. The tool also detects other abnormal behavior that isn’t an incident at the time of detection but may escalate to one. Since its release, MTTR has improved by 45%.
Tech: Java, Apache Math, Python, Scipy, Anomaly Detection, AWS Athena, AWS Kinesis, Kubernetes
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Education
- Computer Science MscTechnical University of Budapest2007The program aims to qualify engineers with solid scientific and technical knowledge related to the professional field of Information Technology who are competent in the design of IT systems and tools and the development and integration of IT systems. The MSc program is also designed to prepare students to carry out and coordinate IT-related research and innovation tasks as well as to continue to PhD studies.
- Statistics and Data Science (MicroMasters)Massachusetts Institute of Technology2022The MicroMasters® program in Statistics and Data Science was developed by MITx and the MIT Institute for Data, Systems, and Society (IDSS). It is a multidisciplinary approach comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning.
Certifications
- Mathematics for Machine Learning SpecializationCoursera2019
- Foundations of Modern FinanceMITx on edX2022