Dmitrij Tichonov
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Quant & AI Engineer | PyTorch, TF, Python, C++
Working at the intersection of AI and quantitative systems. These days I build large-scale GPU training platforms — distributed training across thousand-GPU clusters, multi-node orchestration, the hard parts of scaling deep learning — but my roots are in low-level systems programming — high-frequency C++ at J.P. Morgan — and I've never lost the pull toward quantitative finance and market dynamics. I stay sharp by digging into research across both worlds, and I'm often told I'm good at distilling dense technical ideas into something anyone can follow — whether that's an engineer, a lecture audience, or a non-technical stakeholder.
University of Nottingham
BSc Hons, Computer Science
January 1, 2009 – January 1, 2013
NKKM
Computer Science
January 1, 2002 – January 1, 2008
Levo Karsavino Secondary School
Mature Certificate
January 1, 1997 – January 1, 2009
Open Innovation AI
Lead Software Engineer
December 1, 2024 – Present
Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates · On-site
Oats Technologies Limited
Lead Software Engineer | CTO
February 1, 2018 – August 1, 2024
Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates · Remote
Splyt
Lead Software Engineer | CTO
May 1, 2015 – January 1, 2018
London Area, United Kingdom · On-site
JPMorgan Chase & Co.
Technology Analyst
September 1, 2013 – May 1, 2015
London Area, United Kingdom · On-site
Sirosa Technology Ltd
Technical Architect
September 1, 2012 – July 1, 2013
Greater Nottingham
Barclays
Application Developer
July 1, 2012 – August 1, 2012
Vilnius, Lithuania · On-site
Accenture
Software Engineer
July 1, 2011 – July 1, 2012
London Area, United Kingdom · On-site
NKKM
Lecturer
September 1, 2008 – July 1, 2009
Vilnius, Lithuania · On-site
Building Multimodal Search and RAG
DeepLearning.AI
June 24, 2026 – Present
Bayesian Statistics: From Concept to Data Analysis
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Guided Tour of Machine Learning in Finance
Coursera
June 24, 2026 – Present
Mathematics for Machine Learning: Multivariate Calculus
Coursera
June 24, 2026 – Present
Convolutional Neural Networks in TensorFlow
DeepLearning.AI
June 24, 2026 – Present
Natural Language Processing with Classification and Vector Spaces
DeepLearning.AI
June 24, 2026 – Present
Serverless Machine Learning with Tensorflow on Google Cloud Platform
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Google Cloud Big Data and Machine Learning Fundamentals
Coursera
June 24, 2026 – Present
Google Cloud Fundamentals: Core Infrastructure
EDX Alumni
June 24, 2026 – Present
Sequence Models
DeepLearning.AI
June 24, 2026 – Present
Sequences, Time Series and Prediction
DeepLearning.AI
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Google Cloud Platform Big Data and Machine Learning Fundamentals
Coursera
June 24, 2026 – Present
Natural Language Processing in TensorFlow
DeepLearning.AI
June 24, 2026 – Present
Knowledge Graphs for RAG
DeepLearning.AI
June 24, 2026 – Present
Building Applications with Vector Databases
DeepLearning.AI
June 24, 2026 – Present
Vector Databases: from Embeddings to Applications
DeepLearning.AI
June 24, 2026 – Present
Heterogeneous Parallel Programming
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Fundamentals of Machine Learning in Finance
Coursera
June 24, 2026 – Present
Mathematics for Machine Learning: Linear Algebra
Coursera
June 24, 2026 – Present
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
DeepLearning.AI
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory, moving from traditional software engineering at large financial institutions to leading roles in startups and AI innovation, demonstrates a strong adaptability and a proactive approach to emerging technologies. Their involvement in co-founding a company and architecting platforms from scratch suggests an innovative and ownership-driven mindset. The breadth of skills and project diversity, from fintech to social commerce and advanced AI, indicates a versatile individual who can thrive in dynamic environments. The numerous certifications in ML and deep learning also highlight a commitment to continuous learning and staying current with industry trends, which is a strong cultural fit for a fast-paced, technology-driven organization.
Soft Skills & Operational Fit
The candidate's extensive leadership roles (Lead Software Engineer, CTO) suggest strong project management, team leadership, and strategic thinking abilities. Their experience in co-founding a platform and delivering enterprise integrations indicates an entrepreneurial mindset and client-facing skills. The detailed descriptions of complex system designs imply strong problem-solving and analytical skills. However, without psychometric test results, a definitive assessment of work attitude, stress handling, and direct team collaboration style is not possible.