Vince Jankovics, Machine Learning Developer in United Kingdom
Vince Jankovics

Machine Learning Developer in United Kingdom

Member since October 18, 2018
Vince is an engineer with expertise in machine learning and robotics. He has experience developing autonomous systems and artificial intelligence with an emphasis on perception, decision making, and control. He is fluent in Python and C++ and has worked on a variety of projects as a consultant, helping clients achieve their goals.
Vince is now available for hire




United Kingdom



Preferred Environment

Zsh, Git, Linux, Emacs

The most amazing...

...system I've developed is a generative machine learning model that turned simple sketches into pieces of art.


  • Machine Learning Engineer

    2019 - PRESENT
    VAIC 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 Networks
  • Research Visitor

    2019 - 2020
    City, 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 Networks
  • Machine Learning Engineer

    2017 - 2019
    Cambridge 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 Networks
  • Application Support Engineer

    2016 - 2017
    The 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 Networks
  • Robotics Intern

    2016 - 2016
    • 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 Modeling
  • Student Research Assistant

    2013 - 2014
    University 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++


  • Process Optimization System

    I developed a system to find the optimal distillation sequence and parameters for a specified non-ideal mixture. This dramatically reduces the time it takes for a process engineer to design a system that meets the requirements.

  • Pixel-perfect Instance Segmentation

    I developed a deep learning pipeline for an application that required pixel-perfect segmentation masks for retail. It involved carefully selecting and combining state-of-the-art models to achieve the required performance.

  • AI for Drug Discovery

    I contributed to an industry disruptive startup that aims to solve drug discovery with AI. I worked on software engineering and DevOps for large-scale cluster systems to support the research team and designed and implemented a system architecture that made experimentation more cost-efficient and faster. Also, I proposed architectural changes to the research team regarding generative models.

  • Financial Timeseries Prediction

    I worked on a proof of concept for a financial forecasting model that involved large amounts of unevenly spaced time series data. I developed a PyTorch data loader interface to an SQL data warehouse to efficiently train models at scale and tailored deep learning models.

  • AI Artist Demo

    I worked on a machine learning technology demonstration that turned sketches into pieces of art. I built on top of cutting-edge deep learning architectures using generative adversarial networks to create a system that can hallucinate artistic paintings based on the input edges. I used Python with Tensorflow to build the architecture, implement the data pipeline and facilitate distributed training. Since the work that we've done for clients was confidential, this demo could showcase perfectly the capability of the team, and this demo, in particular, had a significant impact on our presence in the AI consulting domain.

  • Beyond Human Vision Demo

    This technology demonstration aimed to reconstruct distorted images, so the model not only did pixelwise mapping, but it also had to fill in missing information based on the context. Generative adversarial networks are excellent in doing this, and it was shown how the model can change the output depending on the environment, I used Python with Pytorch for the training and a Flask back-end with a Typescript front-end for the deployed system.

  • Artificial Neural Network Based Adaptive Non-linear Control

    I worked on a non-linear controller that is able to learn the system dynamics that it controls. An artificial neural network is trained online to predict the system states to provide better performance than a simple PID algorithm. It was applied to a simple 2 degrees-of-freedom robotic arm to prove the concept. I developed the mechanics and the electronics for the prototype, simulated the dynamics in C++, and deployed the system to a low-cost Atmel microcontroller using Embedded C.

  • Humanoid Walking Robot

    I developed system design for a humanoid walking robot, simulated and prototyped the control algorithm using Simulink. I implemented the Linux middleware for the actuators and sensors on the onboard controller.

  • IMAV 2017 Virtual Challenge

    I worked on the simulation environment for the IMAV drone competition. I used Gazebo, ROS, and Simulink to provide a high-fidelity simulation that can be used to evaluate autonomous flight controllers.

  • Reinforcement Learning-based Crypto Trading Bot

    I developed an RL agent for cryptocurrency trading that uses OHLCV data and technical indicators. The model was trained and backtested with data from the last few years, and it showed promising results, outperforming baseline strategies.

    I evaluated different RL algorithms (PPO, IMPALA) and model architectures (fully connected, convolutional, attention-based) to find the best performing agent.

    I developed the model using PyTorch and Ray, which enables massive scaling to reduce the training time significantly. For backtesting and live trading, I used Freqtrade.


  • Languages

    C++, Python, C, Bash, SQL, Embedded C, Simulink
  • Frameworks

    Swagger, Flask, Boost, Spark
  • Libraries/APIs

    Matplotlib, Pandas, OpenCV, PyTorch, NumPy, Scikit-learn, TensorFlow
  • Paradigms

    Data Science, Agile
  • Platforms

    Linux, Docker, Kubernetes, Google Cloud Platform (GCP), Android, Amazon Web Services (AWS), Azure
  • Other

    Data Analysis, Data Visualization, Deep Learning, Robotics, Machine Vision, Machine Learning, Artificial Intelligence (AI), Generative Adversarial Networks (GANs), Reinforcement Learning, Image Recognition, Computer Vision, Web Scraping, Object Detection, Neural Networks, Machine Learning Operations (MLOps), Convolutional Neural Networks, Engineering, Quantitative Modeling, Mathematical Modeling, Robot Operating System (ROS), Condor, OOP Designs, Natural Language Processing (NLP), Forecasting, Data Engineering, Team Leadership, Unmanned Aerial Vehicles (UAV), Image Processing, Optimization
  • Tools

    Zsh, Oh My Zsh, TensorBoard, Plotly, Git, Spacemacs, MATLAB, Emacs, Docker Compose
  • Storage

    MySQL, MongoDB, Redis


  • Master's Degree in Robotics
    2015 - 2016
    University of Bristol - Bristol, England
  • Bachelor's Degree in Mechatronics
    2012 - 2015
    University of Southern Denmark - Sonderborg, Denmark

To view more profiles

Join Toptal
Share it with others