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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
Mathematics for Machine Learning: Multivariate Calculus
Coursera
June 24, 2026 – Present
Heterogeneous Parallel Programming
Coursera
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
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Google Cloud Platform Big Data and Machine Learning Fundamentals
Coursera
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
Guided Tour of Machine Learning in Finance
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
Vector Databases: from Embeddings to Applications
DeepLearning.AI
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
Natural Language Processing in TensorFlow
DeepLearning.AI
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
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
DeepLearning.AI
June 24, 2026 – Present
Sequence Models
DeepLearning.AI
June 24, 2026 – Present
Sequences, Time Series and Prediction
DeepLearning.AI
June 24, 2026 – Present
Building Multimodal Search and RAG
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
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.