Atarus

Senior Machine Learning Engineer

Atarus

United Kingdom

Accepting Applications Full-time Hybrid LinkedIn
Posted 2 days, 6 hours ago 0 views 0 applications
Job Description

🚀 Senior / Staff ML Platform Engineer

📍 London (Hybrid)

💰 Up to £150k

🏢 Well-funded AI company (£100m+ raised)

We're working with a fast-growing AI company building large-scale infrastructure that powers the training, deployment, and operation of cutting-edge machine learning systems.

They're looking for engineers with strong software engineering fundamentals who have moved into ML infrastructure, platform, or systems engineering roles.

What you'll be doing 👇

  • Building the platforms and services that support ML training and deployment
  • Developing tooling for data processing, experimentation, and model lifecycle management
  • Improving scalability, reliability, and performance across ML infrastructure
  • Building internal platforms used by researchers and applied scientists
  • Working closely with ML teams to productionise new capabilities
  • Designing and maintaining distributed systems operating at scale

What they're looking for 🧠

  • Strong backend software engineering background
  • Experience building production systems in Python and at least one systems language (C++, Java, Go etc.)
  • Experience supporting ML workloads, training pipelines, or inference systems
  • Strong understanding of distributed systems, scalability, and reliability
  • Engineers who enjoy building the infrastructure around machine learning rather than developing models themselves
  • Experience working closely with ML researchers or applied scientists

Tech ⚙️

  • Python, PyTorch
  • Distributed systems
  • Data and ML platforms
  • Ray
  • Cloud \& GPU infrastructure

Why it's interesting 💡

  • Work on the engineering backbone behind cutting-edge AI systems
  • High ownership within a small, senior team
  • Solve complex software and infrastructure challenges at scale
  • Strong commercial traction and significant backing
  • Opportunity to shape the platform powering future AI products
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