Vlad Shmyhlo
ML EngineerMachine Learning Engineer
Cohere
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
training models, writing code
Zaporizhia State Engineering Academy
Master's degree, System software
January 1, 2014 – January 1, 2016
Classic Private University
Master's degree, Law
January 1, 2008 – January 1, 2013
Cohere
Member of Technical Staff (Vision-Language Models)
August 1, 2022 – Present
Greater London, England, United Kingdom
Revolut
Machine Learning Engineer (Computer Vision)
September 1, 2020 – October 1, 2021
London, England, United Kingdom
Ring
Research Engineer (Deep Learning)
February 1, 2019 – September 1, 2020
Kiev Region, Ukraine
XOresearch
Deep Learning Engineer
December 1, 2017 – December 1, 2018
Kiev Region, Ukraine
RubyGarage
Software Engineer (Ruby, JavaScript)
March 1, 2015 – July 1, 2017
Dnipropetrovsk Region, Ukraine
AMgrade
Front-end Developer
August 1, 2014 – March 1, 2015
Zaporizhia Region, Ukraine
Baselines
July 1, 2018 – Present
Idiomatic implementations of common Neural Network architectures in TensorFlow
DenseNet implementation
January 1, 2018 – February 1, 2018
My implementation of "DenseNet" image classification network from "Densely Connected Convolutional Networks" paper (https://arxiv.org/abs/1608.06993) in TensorFlow
RetinaNet implementation
January 1, 2018 – February 1, 2018
My implementation of "RetinaNet" object detection network from "DenselyFocal Loss for Dense Object Detection" paper (https://arxiv.org/abs/1708.02002) in TensorFlow
Transformer implementation
December 1, 2017 – January 1, 2018
My implementation of "Transformer" neural machine translation network from "Attention Is All You Need" paper (https://arxiv.org/abs/1706.03762) in PyTorch
Sequence Models
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Programming Languages, Part B
Coursera Course Certificates
June 24, 2026 – Present
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Coursera Course Certificates
June 24, 2026 – Present
Programming Languages, Part A
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a clear focus on cutting-edge ML research and application, aligning well with a dynamic, innovation-driven environment. The personal projects demonstrate initiative and a passion for the field. The diverse experience across different companies (Cohere, Revolut, Ring) suggests an ability to adapt to various organizational cultures. However, the lack of explicit team-based project descriptions or collaborative experiences makes a full cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate's project history indicates a strong drive for independent learning and implementation of advanced ML concepts. The transition from a software engineering background to specialized ML roles suggests adaptability and a strong learning curve. However, without specific behavioral or communication assessment data, it is difficult to fully assess soft skills and operational fit beyond technical aptitude.