Data Architect at Instructure (2021–)
Lead architect for a data access and analytics platform serving Canvas and other education products.
Our data engineering teams are facilitating internal teams and external partners in getting insights from their data. We are collaborating in acquiring, exposing, modeling, categorizing, and managing data through its life-cycle. We have been creating a data lake, ingesting data from relational and non-relational sources using a combination of change data capture, streaming data and Ed-Tech protocols to external systems. Based on the data gathered in the data lake, we have been developing an analytics suite that helps answer ad-hoc queries, drives dashboards and provides interactive drill-down on data. All of these services are integral to our Learning Platform, which is an accelerator to unifying a heterogeneous product portfolio, and helps the company scale.
Technologies involved: Spark, Apache Hudi, Debezium, PostgreSQL, AWS (e.g. Kinesis, MSK, EMR, EKS, Glue), Scala, Java, Python
Engineering Specialist at Kheiron Medical Technologies (2020–2021)
Senior technology advisor for medical products backed by artificial intelligence.
Backed by a neural network stack, our team had built a product that integrated with hospital systems to help ensure proper breast positioning and diagnose malignancies in mammography digital images. Responsibilities of our engineering team included acquiring and pre-processing images, incorporating machine learning models, visualizing predictions and facilitating the verification and validation process.
My main focus had been designing a scalable cloud-first solution for Kheiron's flagship products Mia and Mia IQ, and ensuring a smooth migration from an earlier monolithic on-premise version, and an evolution from a prototype to a full-fledged product. This had entailed collaborating with Machine Learning, Data Acquisition, Product and Clinical Teams.
Technologies involved: Kotlin, Python, C++, PostgreSQL, TensorFlow, AWS (Lambda, Redshift, S3, SageMaker), Azure
Tech Lead at IBM Watson Media, Budapest (2018–2020)
Lead architect for a closed captioning and video analysis product portfolio, part of the Watson suite for major media companies.
Utilizing artificial intelligence research in speech-to-text, visual recognition and natural language understanding, our team created close to real-time applications that automatically enrich video content with metadata for video indexing and search, as well as provide punctuated transcripts for live broadcast streams in English and Spanish. Our responsibilities ranged from integrating external research assets into our product portfolio to developing our own algorithms for solving complex machine learning problems; spanning the entire software development flow taking code from inception to being deployed as a highly available cloud service. Our solution has been integrated with over 80 stations of the Sinclair Broadcasting Group across the US.
My responsibilities included problem analysis, overall system design, balancing business and engineering objectives, communicating with offering representatives, coordinating the engineering aspects of a multi-site team (mainly Atlanta, Budapest, Haifa), creating inventions (patents), solution design and code review, mentoring.
Technologies involved: Go, C++, Boost, Python, Keras, TensorFlow, SQL, ElasticSearch, Kubernetes, IBM Cloud