• Migrate the Automatic Speech Recognition System (ASR) to FastAPI, following clean code principles, to make the code more readable, extensible, and maintainable.• Move the ASR system from vertical to horizontal architecture using Kubernetes, allowing a very high scalability, and able to attend the high demand of our customers.• Implement AWS DynamoDB using Single Table Design as our NoSQL database, which enable us to attend the high demand of On-Line Transactional Processing (OLTP) of our application.• Export the AWS DynamoDB data to AWS S3, and query it with AWS Athena for On-Line Analytics Processing (OLAP), that enable us to perform big analytical queries over the entire dataset.• Display insightful and customized data in dashboards using AWS QuickSight.• Implement a front-end application using React, with the functionalities to design VoiceBots and ChatBots, run campaigns, show the progress of campaigns in real time, and display embedded dashboards.• Lead the AI team, which uses commercial AI models of Text-to-Speech, Speech-to-Text, Natural-Language-Model and Large-Language-Models. Create and fine-tuned own models and deploy them to production.

• Build a product (Front/Back-End) that handles 200K http requests per day and increases 20% of customers’ productivity.• Migrate to NoSQL DB, Redis and BigQuery for scalability. Use PyTorch for ML and Pandas and Plotly for analytics.• Handle a team of 10 members, use scrum to track progress and keep relations with customers.

• Build a infrastructure based on NodeJs and Angular to run black-box and unit tests automatically or on demand, helping developers to validate fast and easily their work. Introduce code coverage to check if new code is really tested.• Create black-box and unit tests in C/C++, Java and Perl to extend code coverage.• Agile SW development method: play the role of scrum master in the team.

• Ph.D. Thesis: “Hierarchical Neural Network Structures for Phoneme Recognitions”. Implement backpropagation algorithm in C for training several structures of NNs that improves Phoneme Recognition in a Natural Language Processing system.• Publish 2 Patents, 1 Book and 7 papers.

• Master Thesis: “Feature Space Transformation for Speech Recognition”. Implement different linear classifiers such as PCA, LDA and HLDA and select the best under constraints of highly correlated data and small training data.• Build C tools that removes distortions of audio data at the input of a speech recognition system.

• Web site development and research and analysis of web positions.• Assisting the Consulting team, specifying customer requirements and carrying out market research.

• Student supervisor at the laboratory. Some subjects included electric dipole radiation, parameters of antennas and waves propagation.

• Create exercises and tests in MATLAB programming for students. Tasks: Information Theory, Detection and Estimation, and Noise Cancellation.• Give exercise classes to the students.