AI Futures has been engaged to find a Senior AI Platform Engineer for one of the world's largest media and entertainment technology companies. This is a production operations hire at the intersection of MLOps, platform engineering, and applied AI - serving content workflows used by the biggest names in streaming and broadcast.
The company
A global technology company underpins the media and entertainment industry at scale - serving content creators and distributors including the world's leading streaming platforms, studios, and broadcasters. Their AI systems run across media localisation, dubbing, accessibility, and content distribution workflows, processing content for millions of viewers every day.
They are not experimenting with AI. It is in production, at volume, and the infrastructure needs to match.
The role
As a Senior AI Platform Engineer you will own the reliability, scalability, and operational health of production AI services across media, localisation, and workflow automation platforms.
This is not a research role. You are the person who makes sure the model someone else trained actually works - consistently, at scale, under real load. You will sit between the AI engineers building models and the product teams depending on them.
You will build the deployment pipelines, monitoring infrastructure, and release automation that turn prototype AI into something a global media company can stake its operations on.
What you’ll do
- Build and operate platforms for deploying, monitoring, and maintaining production AI models and inference services across media and localisation workflows
- Develop automation for model packaging, promotion, validation, rollout, and rollback - the full release lifecycle
- Implement monitoring, alerting, and observability for AI services covering performance, latency, availability, error rates, and cost
- Partner with AI engineers to move models and agentic workflows from prototype to production reliably and repeatably
- Define operational standards for production AI systems: runbooks, incident response, testing, and release readiness criteria
- Support both batch and real-time AI workloads across speech, translation, and media processing pipelines
- Troubleshoot production issues across model serving, API behaviour, environment configuration, and deployment layers
What you’ll bring
- Production MLOps or AI platform engineering experience - you have operated AI/ML models in a live environment and you have been on the receiving end when an inference service failed at scale
- Python - essential; strong scripting and automation fundamentals across the deployment lifecycle
- Containers, CI/CD, and cloud infrastructure - you know how AI services are packaged, promoted, and run in production
- Model lifecycle management: versioning, validation, rollback, and the operational patterns that prevent silent degradation
- Observability mindset - you instrument before things break, not after
- Model-serving frameworks and MLOps platforms: MLflow, KServe, BentoML, Ray, or equivalent
- LLMs, agentic workflows, RAG systems, ASR, TTS, or machine translation in production
- GPU-backed inference, distributed systems, or high-throughput batch processing
- AWS - compute, storage, networking, security, monitoring, and deployment services
- Experience in media, localisation, dubbing, or content workflow environments
- €105-125k + benefits package
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Platform Engineer Arbeitgeber: AI Futures
Als Arbeitgeber bietet unser Unternehmen eine dynamische und innovative Arbeitsumgebung in Hamburg, die es Ihnen ermöglicht, an bedeutenden Post-Merger-Integrationen zu arbeiten und direkt mit der Führungsebene zusammenzuarbeiten. Wir fördern eine Kultur des kontinuierlichen Lernens und der beruflichen Weiterentwicklung, während wir gleichzeitig ein starkes Teamgefühl und eine transparente Kommunikation pflegen. Mit einem beeindruckenden Wachstum und einer klaren Vision für die Zukunft sind wir bestrebt, unseren Mitarbeitern nicht nur herausfordernde Aufgaben, sondern auch attraktive Karrierechancen zu bieten.
