Staff ML Platform Lead – Gen AI & GPU Infra

Takeaway.com; Amsterdam; On-site; EUR 180,000 - 240,000; Full time

Job summary

Just Eat Takeaway.com is seeking a Staff Machine Learning Engineer to lead the ML infrastructure roadmap and architectural direction for a scalable, hybrid cloud platform powering personalised recommendations and intelligent targeting across multiple markets.

You will own the design of the ML platform, oversee GPU compute strategies, and drive the adoption of Generative AI while balancing performance, cost, and reliability.

Qualifications

• Experience defining and delivering technical roadmaps for large-scale ML platforms.
• Strong background in production ML architecture balancing latency, quality, and cost.
• Experience leading adoption of LLMs from experimentation to production deployment.

Responsibilities

• Own the technical roadmap for the ML infrastructure domain including GPU compute, model serving, training platforms and observability.
• Lead evolution of the foundation model platform in a hybrid AWS/GCP environment.
• Define GPU compute strategy across Kubernetes, Vertex AI and SageMaker.
• Drive production adoption of Generative AI and LLM capabilities with governance and evaluation practices.
• Collaborate with engineering teams to remove blockers and align ML systems with business priorities.
• Provide architectural guidance across multiple teams and mentor engineers to promote engineering excellence.

Skills

Technical roadmaps

ML infrastructure

LLMs / Generative AI

Kubernetes

Model serving

GCP / AWS / Vertex AI / SageMaker

Cross-team leadership

Tools

Kubernetes

Vertex AI

SageMaker

GCP

AWS

Job description

Just Eat Takeaway.com is seeking a Staff Machine Learning Engineer to lead the ML infrastructure roadmap and architectural direction for a scalable, hybrid cloud platform powering personalised recommendations and intelligent targeting across multiple markets.

You will own the design of the ML platform, oversee GPU compute strategies, and drive the adoption of Generative AI while balancing performance, cost, and reliability.