Machine Learning Engineer
2019 - PRESENTVAIC Ltd.- Worked on proofs-of-concept and feasibility studies for machine learning systems.
- Worked on software engineering and DevOps for large-scale cluster systems to support AI research.
- Collaborated on the deployment and commercialization of cutting-edge machine learning algorithms.
- Led a team of three other freelancers to work on a multidisciplinary project that was about designing an industrial IoT device and developing a machine learning system to process the gathered data.
- Hired and coached interns who contributed to both internal and external projects.
Technologies: Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP), Kubernetes, PyTorch, Python, C++, C, Machine Learning, Data Science, Deep Learning, OpenCV, Robotics, Artificial Intelligence (AI), Quantitative Modeling, Data Analysis, Mathematical Modeling, Image Recognition, Computer Vision, MySQL, Web Scraping, Reinforcement Learning, Object Detection, Natural Language Processing (NLP), Forecasting, Neural Networks, Data Engineering, Machine Learning Operations (MLOps), Team Leadership, Convolutional Neural NetworksResearch Visitor
2019 - 2020City, University of London- Worked on neuro-symbolic learning for inductive logic programming problems.
- Built on previously developed code, improving the performance and providing a Python interface for the C++ legacy code.
- Ran large-scale experiments with the proposed model.
Technologies: PyTorch, Python, C++, C, Deep Learning, Machine Learning, Artificial Intelligence (AI), Data Analysis, Data Science, Image Recognition, Computer Vision, Neural Networks, Data Engineering, Convolutional Neural NetworksMachine Learning Engineer
2017 - 2019Cambridge Consultants Limited- Worked on advanced machine learning systems to provide cutting-edge solutions to clients by improving and tailoring state-of-the-art algorithms from academic publications.
- Developed deep learning models using PyTorch and TensorFlow.
- Worked on data collection and preprocessing for imaging problems.
- Developed models for time series and sensor data classification using boosted trees and neural networks.
- Deployed ML systems on edge devices using highly optimized software developed in C++.
- Worked on data mining and processing pipelines using Python.
- Developed tools for monitoring and managing ML training pipelines and large datasets.
- Interviewed and coached interns who contributed to both internal and external projects.
Technologies: TensorFlow, PyTorch, C++, Python, Machine Learning, Deep Learning, Artificial Intelligence (AI), Data Analysis, Data Science, Image Recognition, Computer Vision, MySQL, Web Scraping, Reinforcement Learning, Object Detection, Forecasting, Neural Networks, Data Engineering, Machine Learning Operations (MLOps), Team Leadership, Convolutional Neural NetworksApplication Support Engineer
2016 - 2017The MathWorks- Provided technical support for customers in various fields, e.g. robotics, control systems signal processing, embedded systems, and machine learning.
- Worked on a drone simulation using C++, Matlab, and Simulink.
- Worked on unit testing of new features for the deep learning toolbox.
Technologies: C++, Simulink, MATLAB, Computer Vision, Image Recognition, Neural NetworksRobotics Intern
2016 - 2016DroneX- Worked on software development, using C++ and ROS, to control a UAV platform.
- Developed the control system, simulation and the mechanical test rig for a bipedal robotic system.
- Worked on embedded software design for a real-time power management application on a low-cost microcontroller.
Technologies: Embedded C, C++, Python, Robotics, Mathematical ModelingStudent Research Assistant
2013 - 2014University of Southern Denmark- Worked on the design of a tactile sensitive robotic fingertip and automated test framework for it in C++.
- Developed a machine learning model for sensor characterization.
Technologies: Python, C++