Machine Learning Deep
Resume:
VIEIRA SANTOS
Machine Learning Engineer
Rua Cordovil, Rio de Janeiro - RJ, Brazil [21250-450]
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https://www.linkedin.com/in/vieira-santos-50a878285/ Summary
Innovative Machine Learning Engineer specializing in Deep Learning with a profound understanding of the field, grounded in strong mathematical background. Switching career and 5+ years of experience in diverse DL/ML projects, including Face Recognition, Speech Recognition and NLP, have demonstrated my adaptability to new domains. Consistently upholding a strong moral work ethic, coupled with flexibility and eagerness to learn cutting-edge techniques, has repeatedly contributed to my success throughout my career. I am willing to take new adventures and utilize my professionalism to make a positive impact on the world to make the world a wonderful place. Technical Skills
Programming Languages Python • C/C++ • MATLAB • Java Deep Learning Frameworks Numpy • Scikit-learn • SciPy • Tensorflow • PyTorch • MXNET • Caffe • Keras • Matplotlib • Kaldi
Deep Learning Techniques CNNs • RNNs • Attention Mechanism • GANs • Transfer Learning Cloud Computing Platforms AWS • Google Cloud Platform • Microsoft Azure Career Experience
Inovação Médica Goiânia, Brazil Mar 2023 – Present Machine Learning Engineer, Part-time
Oversaw end-to-end development and deployment of a personalized AI healthcare Assistant.
• Implemented personalized AI healthcare Assistant pipeline using ChatGPT API and LangChain.
• Recommended and supervised fine-tuning of the Portuguese-English translator using medical data, which improved the accuracy by 2.3% in healthcare helpline questions and answers.
• Raised the accuracy of questioning by 3.2% with prompt engineering.
• Tutored 3 interns for a duration of 2 months, giving them the total overview of machine learning project pipeline.
Almawave do Brasil Informática Ltda. São Paulo, Brazil Sep 2019 – Dec 2022 Machine Learning Engineer, Full-time
Upgraded the Text-to-Speech system despite it being a new field to me.
• Enhanced the naturalness by 0.3 on the MOS scale using modern TTS models.
• Added 100 speakers using Transfer Learning, requiring less than 20% of data previously needed training.
Played a key role in developing both online and offline Speech Recognition systems.
• Trained the acoustic model on 23, 000 hours of speech data using Kaldi Framework on Ubuntu environment.
• Reduced the inference time by customizing the model to a smaller size, resulting in a 50% decrease.
• Successfully deployed to the android application, which gained more than 1 million users in 3 months.
• Optimized the language model inference to reduce the memory allocation size by 60% on mobile devices.
UNICAMP Campinas, São Paulo, Brazil Oct 2017 – Sep 2019 Postgraduate Researcher
Participated in various projects as a Deep Learning postgraduate researcher, making substantial contributions.
• Established a face recognition system pipeline including preprocessing, face detection, feature extraction etc.
• Suggested and implemented various methods including center-loss, arc-loss and inception-resnet, resulting in an increase of 1.9% in face verification accuracy.
• Proficiently improved face detection speed by 1.4 times and detected 12 more facial landmarks with greater accuracy using MTCNN methods.
• Integrated an anti-spoofing module based on deep learning, achieving an impressive accuracy of more than 90%.
• Deployed the system to a mobile application by customizing and combining features of 5 smaller models, such as MobileFaceNet v1 and v2 etc.
• Prepared only for 1 month and participated individually in Fake Face Detection Challenge in 2018, taking 6th place.
• Designed and implemented a face dataset refining tool utilizing the aforementioned feature extraction module and clustering algorithms beyond the call of duty, resulting in the removal of 10% of irrelevant face images.
Why Me
• Strong theoretical foundation and practical expertise in ML, especially Deep Learning
• Quick learner and incredibly productive
• Highly responsible and conscientious
Education
• Master of Science in Computer Science, University of Campinas, Campinas Brazil, 2017-2019
• Bachelor of Science in Mathematics, University of Campinas, Campinas Brazil, 2011-2017
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