Ask me anything about Carl

1. Apr 2023 – Present

   Remote

   Co-Founder & CTO

   WithMe

   • Co-founded WithMe, an all-in-one platform for creators, and led engineering from first prototype to a profitable commercial product, helping raise over £600,000 across multiple funding rounds.
   • Designed and built WithMe's AI agent team, a multi-agent system that acts as a back office for each creator. It cut the time to build a creator hub to minutes and saved creators hundreds of hours by automating recurring marketing, sales, support and design work. Otto, a planner agent, delegates tasks to specialist agents (Margo, Sal, Cassie and Dez). The specialists use tools to act on the platform, draw on a shared memory of each creator's brand and audience, and pass key actions to the creator for approval. A feedback system captured creator ratings and edits to refine prompts and evaluation sets.
   • Defined the key product metrics and, through user feedback loops and rapid iteration towards product-market fit, cut monthly churn from 18% to 8% and lifted trial conversion from 32% to 46%.
   • Owned and scaled the full technical architecture across web, mobile, payments, analytics and AI, built on AWS, including a live and recorded video pipeline (IVS, MediaConvert), containerised and serverless back-end services (ECS Fargate, Lambda), and managed data and content delivery (RDS, S3, CloudFront).
   • Hired and mentored a team of three early-career engineers, growing them into engineers who owned production features from design to deployment, through pair programming, code review, CI/CD and shared engineering standards.
2. Dec 2024 – Feb 2026

   Hybrid, London, United Kingdom

   Lead Audio Machine Learning Engineer

   Cantine / Phiona

   • Led the research and development of deep learning models that infer psychological and behavioural traits from audio. This is a hard problem: labelled data is scarce and labels are subjective, so used self-supervised pre-training and representation learning on large unlabelled audio datasets, then fine-tuned Transformer models on smaller annotated sets.
   • Built multimodal and generative models combining audio with behavioural signals, using GANs and other generative approaches for audio synthesis and data augmentation. Designed the full ML pipeline from data collection and annotation through training, statistical evaluation and benchmarking to production deployment.
   • Conducted applied research with University College London (UCL) across audio ML, generative AI and computational psychology, and built and led a team of three engineers, introducing CI/CD, automated testing and experiment tracking to take research models into production.
3. Dec 2020 – Apr 2023

   Hybrid, Windsor, United Kingdom

   Senior Audio Machine Learning Engineer

   Logitech

   • Improved the deep learning speech enhancement model running on thousands of Logitech video conferencing devices worldwide, raising audio quality across real-world rooms, noise conditions and languages. The models ran in real time on low-power embedded chips, processing a new audio frame every 10 ms with compute budgets as low as 2 MFLOPS.
   • Led the end-to-end development of a deep learning dereverberation system that improved PESQ by around 1.0, from model architecture and training through hyperparameter optimisation to production deployment, and prototyped early Transformer and convolutional architectures that shaped later production models.
   • Designed and ran large-scale audio dataset collection and annotation across rooms, devices, languages and noise conditions, and built the evaluation framework and objective metrics used to benchmark every speech enhancement and dereverberation model before release.
4. Jan 2020 – Dec 2020

   Derby, United Kingdom

   Senior Machine Learning Analyst

   Incora / Pattonair

   • Identified new opportunities through top-down analysis and working closely with colleagues, guiding the future direction of the team and business.
   • Delivered a ~£4,000,000 annual working capital reduction by increasing the accuracy of the machine learning forecast engine through new features and more advanced machine learning architectures.
   • Established process, coding, project and testing quality standards across the whole data science team, ensuring high performance output.
5. May 2019 – Jan 2020

   Manchester, United Kingdom

   Machine Learning Specialist

   Music Tribe

   • Developed the first AI application for live sound audio: Channel AI.
   • Lead author and developer of the in-house machine learning library.
   • Championed and led the team on multiple industry-first machine learning projects.
   • Gathered, processed, stored and utilised large amounts of data.
   • Advanced colleagues' machine learning knowledge through presentations.
6. Oct 2018 – May 2019

   Birmingham, United Kingdom

   Research Associate / Software Engineer / Machine Learning Engineer

   Semantic Audio Labs Ltd

   • Pioneered all machine learning and deep learning research and products.
   • Delivered seven state-of-the-art machine learning algorithms.
   • Provided expert advice on the future direction of the company.
   • Participated in all project meetings with company leaders and external stakeholders.

I'm always happy to talk about machine learning, audio AI, or building products. The best way to reach me is by email.