ML Engineer: AI Platform & Deployment - Hybrid

McGregor Boyall
London, GB
HybridCareer-pivot friendly

Why this role

Pace
Fast Paced
Collaboration
High
Autonomy
Medium
Decision Impact
Team
Role Level
Individual Contributor
Career Pivot Friendly
Welcomes transferable skills

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Improved development standards
  • Enhanced model deployment reliability
Typical background
Machine LearningSoftware Engineering

Transferable backgrounds

  • Coming from Data Science
  • Coming from DevOps

Skills & requirements

Required

PythonC++CI/CDMlops

Preferred

DockerKubernetes

Stack & domain

PythonC++CI/CDMlopsFinance

About the role

Original posting from McGregor Boyall

A leading global quantitative fund is looking for a Machine Learning Engineer to enhance how models are built and deployed. The role combines solution architecture, software engineering, and infrastructure, emphasizing automation and CI/CD for machine learning. Responsibilities include improving development standards, collaborating with teams, and contributing to training programs. Ideal candidates possess strong skills in Python/C++, CI/CD, and MLOps concepts.

Join to accelerate model deployment and boost platform reliability.

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Source: McGregor Boyall careers

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