I’m Kumail Haider, an AI Engineer based in London with hands-on experience across production machine learning, deep learning, backend integration, and applied research. I build practical AI products, interpretable computer vision pipelines, and scalable systems that support measurable business outcomes.
Production-focused AI engineer with a strong applied research foundation and a portfolio aligned to real hiring signals.
I recently completed an MSc in Applied Artificial Intelligence with Distinction and have worked on production ML systems, predictive modelling, REST-based deployment, and deep learning research. My work spans customer re-engagement systems, computer vision, optical flow-based modelling, and LLM/RAG applications.
I’m currently targeting AI Engineer, ML Engineer, and applied AI roles across the UK, Europe, Canada, and the US, with interest in fintech, risk, insurtech, computer vision, and product-led AI environments.
Three portfolio anchors that support your positioning as an AI engineer rather than a generic graduate profile.
Developed a novel vision-based framework that transformed SEC 10-K financial ratios into image sequences and modelled temporal evolution using RAFT optical flow and CNN architectures.
Outcome: Achieved 93–95% classification accuracy with ~0.90 recall and interpretable flow-map analysis.
Built predictive models for engagement and renewal probabilities, integrated ML outputs into business workflows, and supported operational decision-making across thousands of gym members.
Outcome: Contributed to ~12–18% improvement in re-engagement and reduced manual intervention via microservices.
Designed retrieval-augmented workflows and structured prompt pipelines for AI-driven career analysis and practical decision support, with deployment-ready thinking around usage tracking and productionisation.
Outcome: Built a portfolio-ready applied AI system aligned with current market demand for agentic products.
Relevant experience across production AI, mentoring, and software engineering.
Designed and deployed AI-driven features, predictive models, ETL pipelines, and REST-based services for production workflows.
Acted as project client and mentor for software engineering teams, improving sprint delivery quality through structured feedback.
Built backend features in C#, improved API stability, and delivered solutions under real client and deployment constraints.
Stack aligned to AI Engineer and applied ML roles.
Open to AI Engineer, ML Engineer, and applied AI opportunities.
I’m currently open to conversations about production ML, computer vision, RAG systems, and AI roles across international markets.
Location: London, United Kingdom
Email: kumailhaiderid@gmail.com
Focus: AI Engineer · ML Engineer · Applied AI