Staff ML Engineer — Hybrid, High-Impact AI Leader

Fitch Group; Manchester; Hybrid; GBP 110.000 - 150.000; Vollzeit

Benefits dieser Stelle

Hybrid work environment

Learning & mobility programs

Retirement planning & tuition support

Zusammenfassung

Fitch Group is seeking a Staff Machine Learning Engineer in Manchester to lead design and delivery of production AI/ML solutions. You will set technical direction, mentor teams, and collaborate with product squads and business partners to integrate advanced AI capabilities into flagship Fitch Group workflows.

The role focuses on scalable AI/ML systems in cloud environments, governance, and measurable business outcomes, with hybrid work structure and strong emphasis on learning and collaboration.

Qualifikationen

• Bachelor's or Master’s degree in a relevant field (CS/ML/Data Science).
• 8+ years of professional AI/ML engineering experience with production-grade solutions.
• Experience building agentic AI workflows, tool integration, monitoring and observability.

Aufgaben

• Oversee design, development, and deployment of scalable AI/ML solutions across flagship products.
• Mentor junior engineers and set coding standards, architecture and execution practices.
• Drive projects and align AI/ML initiatives with business goals across product squads and stakeholders.
• Develop production-quality software in Python and build large-scale data workflows with Airflow.

Kenntnisse

Python programming

Machine Learning

Generative AI

Cloud computing

Docker

Kubernetes

Airflow

AI governance

Stakeholder communication

Ausbildung

Bachelor's or Master's in CS/ML/Data Science

Tools

AWS

Azure

EKS

Jobbeschreibung

Fitch Group is seeking a Staff Machine Learning Engineer in Manchester to lead design and delivery of production AI/ML solutions. You will set technical direction, mentor teams, and collaborate with product squads and business partners to integrate advanced AI capabilities into flagship Fitch Group workflows.

The role focuses on scalable AI/ML systems in cloud environments, governance, and measurable business outcomes, with hybrid work structure and strong emphasis on learning and collaboration.