Skills
AI
Computer Vision
Deep ML
Langchain
LLM
MLFlow
MongoDB
NLP
OpenAI
OpenCV
Pandas
PostgreSQL
Power BI/Tableau
PySpark
Python
PyTorch
Scikit-learn
SparkNLP
Tensorflow
Tensorflow Serve
Location
London, United Kingdom
Skills
AI
Computer Vision
Deep ML
Langchain
LLM
MLFlow
MongoDB
NLP
OpenAI
OpenCV
Pandas
PostgreSQL
Power BI/Tableau
PySpark
Python
PyTorch
Scikit-learn
SparkNLP
Tensorflow
Tensorflow Serve
Location
London, United Kingdom
Skills
AI
Computer Vision
Deep ML
Langchain
LLM
MLFlow
MongoDB
NLP
OpenAI
OpenCV
Pandas
PostgreSQL
Power BI/Tableau
PySpark
Python
PyTorch
Scikit-learn
SparkNLP
Tensorflow
Tensorflow Serve
Location
London, United Kingdom
About Me
AI/ML Engineer and Product Developer with a proven record of leveraging machine learning and deep learning to deliver actionable insights and innovative products to a diverse range of companies. Demonstrated experience in orchestrating end-to-end product lifecycle, from ideation and stakeholder management to deployment. Adept with the Python data stack ecosystem. Proven capability in harnessing MLOps and data-driven strategies to optimise product performance and user engagement.
About Me
AI/ML Engineer and Product Developer with a proven record of leveraging machine learning and deep learning to deliver actionable insights and innovative products to a diverse range of companies. Demonstrated experience in orchestrating end-to-end product lifecycle, from ideation and stakeholder management to deployment. Adept with the Python data stack ecosystem. Proven capability in harnessing MLOps and data-driven strategies to optimise product performance and user engagement.
About Me
AI/ML Engineer and Product Developer with a proven record of leveraging machine learning and deep learning to deliver actionable insights and innovative products to a diverse range of companies. Demonstrated experience in orchestrating end-to-end product lifecycle, from ideation and stakeholder management to deployment. Adept with the Python data stack ecosystem. Proven capability in harnessing MLOps and data-driven strategies to optimise product performance and user engagement.
Data Scientist & AI/ML Engineer
2021 - 2024
Trust App Ltd
Trust specialises in computer vision technology, offering a multi-platform app for automated number plate-based payments, a SaaS platform for nano influencer marketing (14000+ influencers and 70+ brands).
Refined an existing DB to enable product information search via images. Applied few-shot prompting with GPT-3.5 and OCR for precise extraction of product and brand details, enhancing data accuracy and completeness.
Increased the user engagement by 30%, precision@k of recommendation system by 20% and achieved a 16% reduction in the cost per engagement by designing a scene recognition model.
Engineered an automated influencer content analysis tool using SIFT key point detection algorithm; linked to Stripe's API for conditional payment triggering, saving over 100 hours monthly in administration.
Implemented MLOps practices within the team, establishing MLflow for efficient tracking, management, and deployment of machine learning models, thereby streamlining the model development lifecycle.
Analysed user visit frequencies, and stay durations, to identify usage patterns and peak periods for strategic presentations. This analysis played a key role in site valuation, facilitating successful capital raise.
Collaborated directly with the CEO and CTO to establish key performance metrics for nano influencer products, enabling precise tracking and identification of improvement areas.
AI
AWS
Docker
GCP
Langchain
MLFlow
MongoDB
OpenAI
OpenCV
Pandas
PySpark
Python
PyTorch
Scikit-learn
Tensorflow
Tensorflow Serve
ML Engineer/Research Scientist
2019 - 2021
U.S. Dept of Energy
U.S. Department of Energy (DoE) managed research laboratories advance the energy technologies and develop carbon management solutions to ensure sustainable future.
Introduced 'search by topic' functionality to DoE’s knowledge management platform, EDX (3M downloads/ month ). Used SparkNLP for efficient data preprocessing and gensim for developing a language model that converts text documents into vector representations
Developed a spatial DB by detecting and geolocation oil and gas infrastructures from USDA NAIP satellite imagery using YOLO algorithm. Licensed the DB for various R&D and commercial applications.JavaScript, PostgreSQL/PostGIS and QGIS.
Provided consultation in Machine Learning (ML) and Deep Learning (DL) across diverse projects, offering specialised knowledge and strategic guidance.
gensim
Google Earth Engine
Pandas
PostgreSQL
PySpark
Python
PyTorch
Scikit-learn
SparkNLP
SQL
Tensorflow
Co-Founder
2017 - 2019
FAR Technologies (now Enfinite Technologies)
FAR Technologies is an AI consulting company that focuses on upstream oil and gas sector.
Successfully executed projects focused on failure prediction for various pumps (sucker rod, electrical submersible, and plunger rod) and conducted inverse modelling for reservoir characterisation, contributing to a monthly recurring revenue (MRR) of USD 10,000.
Played a key role in securing $75,000 during a seed funding round, leading the technical due diligence process and contributing to successful investment acquisition.
Facilitated strategic partnership with sensor manufacturers and SME contractors.
Managed a team comprising 3 full-time employees and 5 contractors, overseeing project execution and team coordination to drive successful outcomes.
Published peer-reviewed papers and presented at leading oil and gas conferences, leveraging these platforms for business development and industry engagement.
AI
Deep ML
Pandas
Power BI/Tableau
PySpark
Python
PyTorch
Scikit-learn
Data Scientist & AI/ML Engineer
2021 - 2024
Trust App Ltd
Trust specialises in computer vision technology, offering a multi-platform app for automated number plate-based payments, a SaaS platform for nano influencer marketing (14000+ influencers and 70+ brands).
Refined an existing DB to enable product information search via images. Applied few-shot prompting with GPT-3.5 and OCR for precise extraction of product and brand details, enhancing data accuracy and completeness.
Increased the user engagement by 30%, precision@k of recommendation system by 20% and achieved a 16% reduction in the cost per engagement by designing a scene recognition model.
Engineered an automated influencer content analysis tool using SIFT key point detection algorithm; linked to Stripe's API for conditional payment triggering, saving over 100 hours monthly in administration.
Implemented MLOps practices within the team, establishing MLflow for efficient tracking, management, and deployment of machine learning models, thereby streamlining the model development lifecycle.
Analysed user visit frequencies, and stay durations, to identify usage patterns and peak periods for strategic presentations. This analysis played a key role in site valuation, facilitating successful capital raise.
Collaborated directly with the CEO and CTO to establish key performance metrics for nano influencer products, enabling precise tracking and identification of improvement areas.
AI
AWS
Docker
GCP
Langchain
MLFlow
MongoDB
OpenAI
OpenCV
Pandas
PySpark
Python
PyTorch
Scikit-learn
Tensorflow
Tensorflow Serve
ML Engineer/Research Scientist
2019 - 2021
U.S. Dept of Energy
U.S. Department of Energy (DoE) managed research laboratories advance the energy technologies and develop carbon management solutions to ensure sustainable future.
Introduced 'search by topic' functionality to DoE’s knowledge management platform, EDX (3M downloads/ month ). Used SparkNLP for efficient data preprocessing and gensim for developing a language model that converts text documents into vector representations
Developed a spatial DB by detecting and geolocation oil and gas infrastructures from USDA NAIP satellite imagery using YOLO algorithm. Licensed the DB for various R&D and commercial applications.JavaScript, PostgreSQL/PostGIS and QGIS.
Provided consultation in Machine Learning (ML) and Deep Learning (DL) across diverse projects, offering specialised knowledge and strategic guidance.
gensim
Google Earth Engine
Pandas
PostgreSQL
PySpark
Python
PyTorch
Scikit-learn
SparkNLP
SQL
Tensorflow
Co-Founder
2017 - 2019
FAR Technologies (now Enfinite Technologies)
FAR Technologies is an AI consulting company that focuses on upstream oil and gas sector.
Successfully executed projects focused on failure prediction for various pumps (sucker rod, electrical submersible, and plunger rod) and conducted inverse modelling for reservoir characterisation, contributing to a monthly recurring revenue (MRR) of USD 10,000.
Played a key role in securing $75,000 during a seed funding round, leading the technical due diligence process and contributing to successful investment acquisition.
Facilitated strategic partnership with sensor manufacturers and SME contractors.
Managed a team comprising 3 full-time employees and 5 contractors, overseeing project execution and team coordination to drive successful outcomes.
Published peer-reviewed papers and presented at leading oil and gas conferences, leveraging these platforms for business development and industry engagement.
AI
Deep ML
Pandas
Power BI/Tableau
PySpark
Python
PyTorch
Scikit-learn
Data Scientist & AI/ML Engineer
2021 - 2024
Trust App Ltd
Trust specialises in computer vision technology, offering a multi-platform app for automated number plate-based payments, a SaaS platform for nano influencer marketing (14000+ influencers and 70+ brands).
Refined an existing DB to enable product information search via images. Applied few-shot prompting with GPT-3.5 and OCR for precise extraction of product and brand details, enhancing data accuracy and completeness.
Increased the user engagement by 30%, precision@k of recommendation system by 20% and achieved a 16% reduction in the cost per engagement by designing a scene recognition model.
Engineered an automated influencer content analysis tool using SIFT key point detection algorithm; linked to Stripe's API for conditional payment triggering, saving over 100 hours monthly in administration.
Implemented MLOps practices within the team, establishing MLflow for efficient tracking, management, and deployment of machine learning models, thereby streamlining the model development lifecycle.
Analysed user visit frequencies, and stay durations, to identify usage patterns and peak periods for strategic presentations. This analysis played a key role in site valuation, facilitating successful capital raise.
Collaborated directly with the CEO and CTO to establish key performance metrics for nano influencer products, enabling precise tracking and identification of improvement areas.
AI
AWS
Docker
GCP
Langchain
MLFlow
MongoDB
OpenAI
OpenCV
Pandas
PySpark
Python
PyTorch
Scikit-learn
Tensorflow
Tensorflow Serve
ML Engineer/Research Scientist
2019 - 2021
U.S. Dept of Energy
U.S. Department of Energy (DoE) managed research laboratories advance the energy technologies and develop carbon management solutions to ensure sustainable future.
Introduced 'search by topic' functionality to DoE’s knowledge management platform, EDX (3M downloads/ month ). Used SparkNLP for efficient data preprocessing and gensim for developing a language model that converts text documents into vector representations
Developed a spatial DB by detecting and geolocation oil and gas infrastructures from USDA NAIP satellite imagery using YOLO algorithm. Licensed the DB for various R&D and commercial applications.JavaScript, PostgreSQL/PostGIS and QGIS.
Provided consultation in Machine Learning (ML) and Deep Learning (DL) across diverse projects, offering specialised knowledge and strategic guidance.
gensim
Google Earth Engine
Pandas
PostgreSQL
PySpark
Python
PyTorch
Scikit-learn
SparkNLP
SQL
Tensorflow
Co-Founder
2017 - 2019
FAR Technologies (now Enfinite Technologies)
FAR Technologies is an AI consulting company that focuses on upstream oil and gas sector.
Successfully executed projects focused on failure prediction for various pumps (sucker rod, electrical submersible, and plunger rod) and conducted inverse modelling for reservoir characterisation, contributing to a monthly recurring revenue (MRR) of USD 10,000.
Played a key role in securing $75,000 during a seed funding round, leading the technical due diligence process and contributing to successful investment acquisition.
Facilitated strategic partnership with sensor manufacturers and SME contractors.
Managed a team comprising 3 full-time employees and 5 contractors, overseeing project execution and team coordination to drive successful outcomes.
Published peer-reviewed papers and presented at leading oil and gas conferences, leveraging these platforms for business development and industry engagement.
AI
Deep ML
Pandas
Power BI/Tableau
PySpark
Python
PyTorch
Scikit-learn
How it Works
Hiring Made Simple
1
Talk to One of Our Engineers
An engineer on our team will work with you to understand your goals, technical needs, and your company culture.
2
Review Candidates
Within days, we'll introduce you to the right talent for your project hand picked by our experts.
3
The Right Fit
Once you are happy with the candidate, they can immediately start working on your project.
How it Works
Hiring Made Simple
1
2
3
Talk to One of Our Engineers
An engineer on our team will work with you to understand your goals, technical needs, and your company culture.
Review Candidates
Within days, we'll introduce you to the right talent for your project hand picked by our experts.
The Right Fit
Once you are happy with the candidate, they can immediately start working on your project.
FAQ
Frequently Asked Questions
Who are you?
Where are your talents located?
What type of companies do you work with?
What happens if I’m not satisfied with an Aya talent?
Do I have to sign a contract?
Are there any upfront recruiting or contractual costs?
FAQ
Frequently Asked Questions
Who are you?
Where are your talents located?
What type of companies do you work with?
What happens if I’m not satisfied with an Aya talent?
Do I have to sign a contract?
Are there any upfront recruiting or contractual costs?