Thomas is currently unavailable
Thomas James Cartwright
Verified Expert in Engineering
Machine Learning Engineer and Developer
Edinburgh, United Kingdom
Toptal member since July 17, 2020
Bio
Thomas has three years of industry experience designing, developing and productionising machine learning solutions and five years of industry experience developing software solutions. He holds a Master of Science in AI (with merit) from the University of Edinburgh, specialising in traditional machine learning, deep learning, and reinforcement learning. Due to a keen interest in entrepreneurship, Thomas joined Toptal to contribute his expertise and explore new challenges.
Portfolio
BlackRock
Amazon Web Services (AWS), Artificial Intelligence (AI), Data Science, Python...
Getaroom
Amazon Web Services (AWS), Keras, NumPy, TensorFlow, Python
Barrachd
SQL, NumPy, Python
Experience
- Python - 8 years
- Data Science - 4 years
- Machine Learning - 4 years
- Deep Neural Networks (DNNs) - 3 years
- Artificial Intelligence (AI) - 3 years
- Recommendation Systems - 2 years
- Reinforcement Learning - 1 year
- Amazon Web Services (AWS) - 1 year
Work Experience
Machine Learning Engineer
2021 - PRESENT
BlackRock
- Developed and productionized machine learning models to predict financial instrument prices using Scikit-learn, PyTorch, NumPy, Pandas, Python, Docker, and AWS.
- Managed stakeholder relationships by scoping project requirements, designing key success metrics, specifying timelines, and presenting findings.
- Led the introduction of Agile processes for new and existing machine learning projects.
- Presented model designs and results to technical and non-technical stakeholders.
- Engineered a model backtesting and monitoring framework using Python, Docker, and AWS—EC2, SageMaker, and CloudWatch.
Technologies: Amazon Web Services (AWS), Artificial Intelligence (AI), Data Science, Python, PyTorch, NumPy, Pandas, Docker, Scikit-learn
Machine Learning Engineer
2019 - 2021
Getaroom
- Improved and productized a deep learning NLP model—achieving a classification accuracy of over 95%.
- Designed and implemented new models for predicting sales of new properties, therefore making property price collection more accurate and efficient.
- Performed an analysis on large, noisy datasets before presenting the findings to nontechnical teams.
- Increased the performance of existing machine learning models through parallelization, the user of GPUs, and refactoring of Python code.
- Ensured AI/ML solutions are explainable to nontechnical members of staff.
- Wrote efficient Athena queries on large, noisy datasets for data analysis and development.
Technologies: Amazon Web Services (AWS), Keras, NumPy, TensorFlow, Python
Software Developer
2017 - 2019
Barrachd
- Developed an online app using Python (NumPy, SciPy), C# .NET, JavaScript, React, and SQL.
- Led the design and implementation of a microservice that matched large volumes of incoming messages to complex queries. Using advanced Python and linear algebra, this service decreased processing time from minutes to less than one second.
- Participated in the design and implementation of a component that clustered large volumes of incoming messages, therefore streamlining the data processing pipeline.
- Worked in a team to implement data analytics software that allowed users to visualize and analyze data from millions of social media interactions every hour. This allowed clients to gain actionable insights from large volumes of unorganized data.
- Developed integrations with a large number of social media APIs, ensuring minimal data was collected to keep operational costs low and ensure clients only saw relevant information.
- Presented and described technically complex components to technical and nontechnical members of the team.
Technologies: SQL, NumPy, Python
QA Lead | Software Developer
2014 - 2017
RotaGeek
- Initiated and led the entire testing process leading to fewer bugs, a more robust product, and a faster development cycle.
- Chose the software release dates, balancing customer requirements with product quality.
- Gathered feedback from clients to align future product developments with client needs.
- Communicated and demonstrated the product to technical and non-technical stakeholders.
Technologies: Python, SQL
Project History
Recommendation System for Citizen Science
https://github.com/tjcdev/qc-recommenderA system that recommends new SciStarter projects to users on the Citizen Science web portal. The recommender system uses the user's previously completed projects, and the contents of projects, to build a profile of users interests.
The unsupervised task clustering and user recommendation system on the SciStarter website was used to increase engagement and the quality of user task completion.
The unsupervised task clustering and user recommendation system on the SciStarter website was used to increase engagement and the quality of user task completion.
Education
2017 - 2019
Master's Degree in Artificial Intelligence
University of Edinburgh - Edinburgh, Scotland
2010 - 2014
Bachelor's Degree in Mathematics
University of Edinburgh - Edinburgh, Scotland
Certifications
JULY 2017 - PRESENT
Machine Learning Specialization
Coursera
Skills
Libraries/APIs
Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn, Keras
Languages
Python, SQL, C#
Platforms
Amazon Web Services (AWS), Docker
Storage
Google Cloud
Other
Recommendation Systems, Machine Learning, Artificial Intelligence (AI), Data Engineering, Deep Neural Networks (DNNs), Data Science, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Reinforcement Learning
Collaboration That Works
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
Share your needs
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
Choose your talent
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
Start your risk-free talent trial
Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.
Top talent is in high demand.
Start hiring