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Saed Hussain

@saedhussain

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AI engineering leader delivering production GenAI, ML forecasting, and agentic systems.

United Kingdom

Message

What I'm looking for

I’m looking to lead production GenAI/ML initiatives—building reliable agentic systems, RAG pipelines, and automated evaluation loops—while mentoring teams and delivering measurable impact in enterprise products.

I’m an AI engineering leader with 10+ years delivering production machine learning and GenAI systems across enterprise SaaS, fintech, IoT, and aerospace. As a Staff ML Engineer at Sage, I lead multi-team initiatives in demand and inventory forecasting, built and productionised NER models for invoice automation, and drive LLM/RAG adoption through team upskilling. I also design and deploy LLM-powered solutions—including an auto-labelling engine using RAG, hybrid search (SPLADE, BM25), and ensemble techniques, plus agentic workflows with structured tool calling.

I’m meticulous about reliability: I’ve built automated evaluation loops using deterministic metrics and LLM-as-a-Judge to assess agent quality, grounding, latency, and regression risk. Previously, I embedded machine learning into an IoT leak detection platform at Leakbot.io on GCP, supported experimentation best practices at Sky Group, and taught practical data science for IoT at the University of Oxford. With a PhD in Engineering (Deep Learning for Aircraft Control Systems), I bring research rigor to real-world engineering—mentoring engineers and aligning technical decisions to measurable business outcomes.

Experience

Work history, roles, and key accomplishments

Current

Fellow — AI Strategy & Applied ML

Current

QA.com

Jan 2025 - Present (1 year 7 months)

Recognised for expertise in AI strategy, applied AI, generative AI, and agentic systems, including technical upskilling.

AI Strategy Applied AI Generative AI Agentic Systems

Current

AI Consultant

Current

Freelance

Sep 2024 - Present (1 year 11 months)

Provided hands-on AI engineering and advisory services focused on agentic applications, LLM evaluation, and production-ready GenAI systems. Designed multi-step agentic workflows and evaluation pipelines using deterministic checks and LLM-as-a-Judge.

AI Agentic Workflow Tool calling Structured Outputs Human In The Loop LLM Evaluation LLM As A Judge RAG

Current

Staff ML Engineer

Current

Sage AI

Jan 2022 - Present (4 years 7 months)

Led multi-team ML and analytics initiatives for demand and inventory forecasting, and built production NER models for invoice automation. Designed and deployed LLM/RAG and agentic AI solutions (including evaluation loops using LLM-as-a-Judge) and line-managed/mentored engineers.

Machine Learning Forecasting Demand Forecasting Inventory Forecasting Invoice Management LLM Hybrid Search BM25 LLM As A Judge Latency Evaluation

Founder (Climate Tech)

Carbon13

Sep 2025 - Nov 2025 (2 months)

Selected for the Carbon13 Venture Builder programme, exploring early-stage climate tech venture concepts and assessing technical feasibility, impact potential, and venture fit.

Guest Lecturer (Data Science and IoT)

University of Oxford

Jan 2018 - Dec 2022 (4 years 11 months)

Delivered practical modules for the “Data Science for the Internet of Things (IoT)” programme, including co-teaching ML sessions with industry experts. Contributed to curriculum development and supported engagement with the industrial AI community.

Data Science Machine Learning IoT Teaching Curriculum Development

Senior Data Scientist

Leakbot.io

Oct 2019 - Jan 2022 (2 years 3 months)

Led the transformation of Leakbot’s IoT platform by embedding machine learning to support home insurance use cases and leak detection. Implemented an end-to-end ML pipeline on GCP and designed scalable CI/CD architecture using Cloud Composer, Dataflow, and AI Platform, including real-time access via GCP App Engine.

Machine Learning IoT Leak Detection GCP Cloud Composer Dataflow CI CD

Data Scientist

Sky Group

Jun 2019 - Oct 2019 (4 months)

Worked in the central analytics team delivering data science solutions for business operations across Sky Mobile, Broadband, and Cinema. Developed and deployed ML models using GCP and promoted best practices for experimentation and reproducibility.

Machine Learning GCP Experimentation Stakeholder Management Data Science

Data Scientist (Consultant)

FutureText AI Labs

Jan 2018 - May 2019 (1 year 4 months)

Provided data science consulting to UK SMEs on practical AI applications across healthcare, media, and robotics. Built deep learning prototypes with Keras and Python and developed conversational AI systems showcased at London meetups.

Python Keras Deep Learning Conversational AI Robotics Business to AI Solution Design

Early Career Highlights

Thales Group

Jan 2015 - Jan 2019 (4 years)

Held multiple technical and strategic roles across Avionics, Research, and Ground Transportation, contributing to AI and IoT innovation in defence, aviation, and transport. Led AI prototyping and deep learning initiatives, developed NLP/chatbot-controlled IoT PoCs using Python/Raspberry Pi/Arduino/AWS Lex, and implemented CI pipelines with Jenkins/Jira/Subversion.

AI Prototyping Deep Learning NLP Chatbot IoT Python Raspberry Pi Arduino Embedded Systems C CI CD Jenkins Jira Market Analysis

Research Associate (Drone Systems)

University of Central Lancashire

Dec 2014 - Jul 2015 (7 months)

Supported the GAMMA programme by developing technical prototypes and conducting market research for consumer and commercial drone technologies. Built prototypes for low-cost aerial tracking using C# and OpenCV and developed follow-me autonomous drone systems for Android/embedded platforms.

Market Research Prototyping C#OpenCV Aerial Tracking Android

Education

Degrees, certifications, and relevant coursework

University of Central Lancashire

PhD in Engineering, Deep Learning for Aircraft Control Systems

2011 - 2015

BAE Systems–funded PhD research in deep learning for adaptive aircraft flight control using neural networks. Published peer-reviewed research in top conferences and journals (available on request).