Achilleas Athanasiou Fragkoulis

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Staff ML Platform Engineer

I’m a Staff ML Platform Engineer based in the UK, currently at Satalia (WPP), where I work on building scalable, production-grade platforms for agentic and GenAI workflows.

My work sits at the intersection of machine learning, distributed systems, and cloud infrastructure, with a strong focus on enabling teams to ship ML and GenAI systems safely, reliably, and at scale.

I’m passionate about

  • ML platforms, MLOps & developer enablement ☁️
  • GenAI systems: agents, RAG, evaluation & governance
  • Cloud-native infrastructure (Kubernetes, IaC, service meshes)
  • Experimentation, observability & reliability in ML systems

What I’m working on at the moment

I’m leading infrastructure and platform efforts across multiple teams to deliver a self-serve ML & GenAI Platform as a Service, supporting large-scale investment in agentic workflows.

This includes:

  • Kubernetes-based platforms (serverless with Knative, Istio service mesh)
  • CI/CD, templates, and reusable internal libraries
  • LLM observability, monitoring and governance (Langfuse, LiteLLM, safety tooling)
  • Production GenAI workloads (LLMs, multimodal, RAG) running on GPUs

Professional experience

I have hands-on experience designing, building, and operating end-to-end ML and GenAI systems in production, from experimentation and modeling through to deployment, monitoring, and governance.

Previously, I’ve:

  • Led development of large-scale experimentation platforms (A/B/n, switchbacks, bandits)
  • Owned ML systems serving thousands of users and customers
  • Built forecasting, cancellations, and time-series models in hospitality and travel
  • Worked on computer vision systems and applied reinforcement learning
  • Acted as technical lead and mentor across ML, MLOps, and platform teams

My career spans industries including advertising, hospitality, ride-hailing, travel, and large-scale consumer platforms.

Teaching & mentoring

I regularly mentor engineers and data scientists on ML systems, MLOps best practices, and platform design. Earlier in my career, I delivered the Data Analytics for Managers course at Product School in London.

Background

I started out in Experimental Particle Physics, working with research groups affiliated with CERN and DESY, before transitioning into industry ML and platform engineering.

Outside of work, I spend most of my time chasing wind and waves 🏄, training 🏋️, and racing the occasional amateur triathlon 🏊🚴🏃