Daniel Tunnermann
Verified Expert in Engineering
Back-end Developer
Anápolis - Goiás, Brazil
Toptal member since October 5, 2022
Daniel is a software engineer with over a decade of experience delivering back-end and full-stack projects. With a master's degree in computer science, he incorporated machine learning into his projects, including natural language processing and speech models. Daniel's primary programming languages are Python and Java, but he is adept at applying other skills to deliver results.
Portfolio
Experience
- Algorithms - 12 years
- Data Structures - 12 years
- Python - 6 years
- Natural Language Processing (NLP) - 4 years
- Machine Learning - 4 years
- Chatbots - 4 years
- OpenAI GPT-4 API - 1 year
- Retrieval-augmented Generation (RAG) - 1 year
Preferred Environment
Visual Studio Code (VS Code), Linux, Python 3, FastAPI, SQL, PyTorch, NumPy, Pandas, Scikit-learn
The most amazing...
...application I've developed is an intelligent chatbot with more than a million users.
Work Experience
Senior AI Engineer/Software Engineer
Akad Seguros
- Developed a chatbot with OpenAI GPT LLMs (WhatsApp with a Python back end) for insurance brokers that is serving thousands of users per month. The chatbot uses Retrieval Augmented Generation (RAG) to answer with info from internal docs.
- Developed an AI tool for human customer services transferred from the chatbot, including a front end in JavaScript and a back end in Python. It connects to Meta WhatsApp API to continue conversations where the chatbot handles control to the human.
- Developed a question-answer tool with OpenAI GPT LLMs (a Python back end) for internal users to answer customer service calls. The tool uses Retrieval Augmented Generation (RAG) to reply with info from internal docs, including previous customer interactions.
- Developed autonomous agents with OpenAI LLMs and LangChain to process previous customer services, summarizing and extracting information, checking correctness and attendance to guidelines, and feeding the internal Q&A tool.
Senior Software Engineer
Department of Federal Revenue of Brazil
- Developed question-answer chatbots used by millions, reducing the need for human experts, which is particularly helpful in COVID-19 times, using Python, PyTorch, Hugging Face, and FastAPI.
- Built a system in Java to control international collaboration demands that helped keep track of deadlines and the history of the institution's global partnerships.
- Engineered a predictive model for fraud detection in tax returns using Python, Project Jupyter, and scikit-learn.
- Worked as the institution's chief of development, implementing a software development process, standardizing tools, and managing development projects.
- Taught data science and AI courses for dozens of employees. During the pandemic, these courses were held online.
Senior Software Engineer - Machine Learning
CyberLabs
- Built neural text-to-speech models using Python and PyTorch, with a mean opinion score of 4.4 out of five, comparable to human speech.
- Created a speaker verification model with 99.6% accuracy in the internal dataset. Used Python and PyTorch for training the model and TorchServe to serve it.
- Developed the back end using Python to serve these models with APIs hosted on AWS.
- Designed the preprocessing pipeline for the speaker verification model, with deep fake detection with 96% accuracy, noise reduction, and audio length validation.
Experience
Chatbot for the Brazilian Tax Agency
Education
Master's Degree in Computer Science
Federal University of Goiás - Goiânia, Goiás, Brazil
Bachelor's Degree in Computer Science
University of Brasília - Brasília, Federal District, Brazil
Skills
Libraries/APIs
PyTorch, NumPy, Pandas, Scikit-learn
Tools
Git, Docker Swarm
Languages
Python, SQL, Java
Frameworks
Spring
Platforms
Visual Studio Code (VS Code), Linux, Docker
Storage
Databases, MongoDB
Other
Software Engineering, Algorithms, Data Structures, Natural Language Processing (NLP), OpenAI GPT-4 API, Chatbots, APIs, Back-end, OpenAI GPT-3 API, FastAPI, Retrieval-augmented Generation (RAG), System Design, Architecture, Programming, Artificial Intelligence (AI), Neural Networks, Machine Learning, Speech Synthesis, Generative Pre-trained Transformers (GPT), OpenAI, Large Language Models (LLMs), LangChain
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