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I'm Joshua Bailey, a Generative-AI specialist and hands-on Machine Learning Engineer with 6+ years designing, shipping and scaling NLP and multimodal systems.\n\nMy recent work focuses on taking LLM-driven products to market, including financial coaching (Munny), ad-tech automation (Three&Six), Job Description Analysis (JobFair), Executive Coaching (Manageable), and 2D-to-3D asset conversion. I excel in Python, PyTorch, vector databases, AWS and GCP, and the full MLOps lifecycle. I was honoured to win the AWS GenAI Hackathon for innovative GenAI UX.…I'm Joshua Bailey, a Generative-AI specialist and hands-on Machine Learning Engineer with 6+ years designing, shipping and scaling NLP and multimodal systems.\n\nMy recent work focuses on taking LLM-driven products to market, including financial coaching (Munny), ad-tech automation (Three&Six), Job Description Analysis (JobFair), Executive Coaching (Manageable), and 2D-to-3D asset conversion. I excel in Python, PyTorch, vector databases, AWS and GCP, and the full MLOps lifecycle. I was honoured to win the AWS GenAI Hackathon for innovative GenAI UX.

Joshua Bailey

Data Scientist, AI Engineer, Developer, +4

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I'm Joshua Bailey, a Generative-AI specialist and hands-on Machine Learning Engineer with 6+ years designing, shipping and scaling NLP and multimodal systems.\n\nMy recent work focuses on taking LLM-driven products to market, including financial coaching (Munny), ad-tech automation (Three&Six), Job Description Analysis (JobFair), Executive Coaching (Manageable), and 2D-to-3D asset conversion. I excel in Python, PyTorch, vector databases, AWS and GCP, and the full MLOps lifecycle. I was honoured to win the AWS GenAI Hackathon for innovative GenAI UX.…I'm Joshua Bailey, a Generative-AI specialist and hands-on Machine Learning Engineer with 6+ years designing, shipping and scaling NLP and multimodal systems.\n\nMy recent work focuses on taking LLM-driven products to market, including financial coaching (Munny), ad-tech automation (Three&Six), Job Description Analysis (JobFair), Executive Coaching (Manageable), and 2D-to-3D asset conversion. I excel in Python, PyTorch, vector databases, AWS and GCP, and the full MLOps lifecycle. I was honoured to win the AWS GenAI Hackathon for innovative GenAI UX.

Available to hire

I’m Joshua Bailey, a Generative-AI specialist and hands-on Machine Learning Engineer with 6+ years designing, shipping and scaling NLP and multimodal systems.\n\nMy recent work focuses on taking LLM-driven products to market, including financial coaching (Munny), ad-tech automation (Three&Six), Job Description Analysis (JobFair), Executive Coaching (Manageable), and 2D-to-3D asset conversion. I excel in Python, PyTorch, vector databases, AWS and GCP, and the full MLOps lifecycle. I was honoured to win the AWS GenAI Hackathon for innovative GenAI UX.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Director and Lead AI Engineer at Sqwosh

April 1, 2024 - Present

Director and Lead AI Engineer responsible for automating Paid Search and SEO tools, introducing a GPT-4 powered Google Ads management system with a 25% performance uplift, and an SEO content generator reducing development time by 60%. Led the Financial Literacy App using Agentic workflows with OpenAI APIs, serving over 5,000 users. Implemented vector databases and prompt engineering to improve AI reliability by 30%, and collaborated with finance advisors to ensure regulatory compliance.

Senior Data Scientist at Relative Insight

July 1, 2024 - October 3, 2025

Productionised NER, POS and aspect-based sentiment pipelines (spaCy, Transformers) behind AWS REST APIs; boosted F1 by 20% and tripled inference speed. Built an ML OCR/ETL module automating 60% of client uploads, halving time-to-insight. Mentored 3 DS/ML engineers and established code-review and experiment-tracking practices to cut tech debt.

Data Scientist at Behavioural Insights Team

September 1, 2019 - October 3, 2025

Developed an RNN model in PyTorch for predicting gambling severity, boosting AUC from 0.82 to 0.93 to aid early intervention strategies.

Director and Lead AI Engineer at Sqwosh

April 1, 2024 - Present

Automated Digital Tools: Developed innovative tools for Paid Search and SEO services, enhancing client onboarding and management efficiency by 40%. Google Ads Automation: Engineered a GPT-4 powered Google Ads management system, automating ad creation and deployment, leading to a 25% increase in ad performance. SEO Content Generator: Created an SEO content generator using OpenAI API and Google's Events API, reducing content development time by 60%. Financial Literacy App: Designed and developed a financial literacy app utilising Agentic workflows with OpenAI's APIs and new Agents SDK, providing automated financial advice and budgeting support to over 5,000 users. Advanced AI Techniques: Implemented vector databases and prompt engineering to enhance AI reliability and accuracy by 30%. Regulatory Compliance: Collaborated with finance and debt advisors to align chatbot functionalities with regulatory standards, improving user trust and compliance.

Senior Data Scientist at Relative Insight

July 1, 2024 - October 3, 2025

Language Intelligence Platform: Productionised NER, POS and aspect-based sentiment pipelines (spaCy, Transformers) behind AWS REST APIs; boosted F1 20%, tripled inference speed. Text Extraction Service: ML OCR/ETL module now auto-processes 60% of client uploads, halving time-to-insight. Prototype Lab: Rapidly shipped demos that drove 15% feature-adoption uplift, incl. early GenAI RAG proof-of-concept adopted in 2023 roadmap. Mentored 3 DS/ML engineers; instituted code-review and experiment tracking practices that cut tech debt sprint rollover 30%.

Data Scientist at Behavioural Insights Team

September 1, 2019 - October 3, 2025

Problem Gambling Prediction: Developed an RNN model in PyTorch for predicting gambling severity, boosting AUC from 0.82 to 0.93, aiding in early intervention strategies.