01. About
I am a Machine Learning Engineer focused on the intersection of infrastructure, data, and modelling. My work revolves around building robust systems that enable the "Agentic Web," where AI agents can reliably operate, communicate, and execute complex workflows.
Currently, I'm simplifying the unification of Code and AI, designing protocols that allow agents to be more than just chat bots.
02. Stack
Languages
PythonTerraform
ML Frameworks & Serving
PyTorchFastAPILangChainAgent SDKsOpenTelemetryMCPONNX
Orchestration & Data
SkyPilotAWS/GCPTraining Job OrchestrationApache BeamDagster/AirflowTemporal
Compute & Infrastructure
KubernetesDocker
03. Experience
Staff Engineer
Scale AI
May 2025 - PresentLondon, U.K.
Principal MLOps Engineer + Platforms Team Lead
Papercup AI
Jan 2023 - May 2025London, U.K.
- Designed and led the ML cloud training stack from scratch with ClearML and Skypilot, scaling compute from 16 to 50 GPUs.
- Led an initiative to migrate the model serving stack to be serverless, reducing idle cost time by 90%. Built an internal library to create consistent interfaces, conventions and OpenTelemetry tracing.
- Designed and led an initiative to increase data processing speeds by 50x using Apache Beam with GCP's Dataflow using 250+ GPUs.
- Implemented a tool using GPT-4 and LangChain to automate creative text generation, reducing data acquisition time from ~4 months to ~2 weeks.
- Automated and productionized a transcription and translation workflow using Deepgram, GPT-4, LangChain, Temporal, FastAPI and Streamlit, allowing the asynchronous system to serve 1000% more workflows per day.
- Created the foundational Platforms team (SREs, MLOps, Data Engineers) and hired two MLOps engineers to the team.
Senior Machine Learning Engineer
Zenith AI (Acquired by Opentrons)
Oct 2020 - Jan 2023Belfast, U.K.
- Founding engineering team member, company acquired after 9 months.
- Reduced cumulative QA build time from 2800 minutes to 200 minutes per week by optimizing Docker builds.
- Designed an async queue-based graph executor reducing ML load time from 3 hours to 35 minutes.
- Led a team implementing secure self-service ML web app deployments, cutting wait times from 3 days to 15 minutes.
Applied Computer Vision Researcher
AnyVision (Now Oosto)
Sep 2019 - Oct 2020Belfast, U.K.
- Developed a Focus of Attention system for retail using 3D geometry and depth estimation.
- Built a defect classification prototype in 48 hours, later piloted by a major electrical company.
- Introduced a benchmark-driven-development research philosophy with Grafana analytics.
Image Processing Consultant @ HP
Altran (Acquired by Capgemini)
Mar 2017 - Sep 2019Barcelona, Spain
- Supported the creation of a Python-based middleware for large format printers.
- Implemented sensor-based calibration routines for large format and 3D printers.
- Built internal tools to identify and fix calibration bugs, halving debugging time for R&D.
04. Education
PhD Student and Teaching Assistant
May 2013 - Feb 2017Computer Vision Center
Implemented Slither, a random forest framework for semantic segmentation using C++ and Python.
MSc. Computer Vision
Sep 2011 - Sep 2012University of Sheffield
Worked on face recognition, traffic analysis, and FPGA-based cryptography.
B.E. in Electronics and Communication
Aug 2007 - May 2011Manipal Institute of Technology
Internships at FH Westkueste, Germany (2011) and mdirect, Tunisia (2009).