Experienced and forward-thinking Head of ML Ops required to lead the design, development, and scaling of cutting‑edge machine learning operations within a high‑impact, data‑driven environment. This is a unique opportunity to shape ML Ops strategy, mentor a growing team, and drive best‑in‑class practices across the full ML lifecycle.
The Role
As Head of ML Ops, you will take ownership of building and evolving robust, scalable, and production‑ready ML systems. You’ll play a key role in bridging data science and engineering, ensuring seamless deployment, monitoring, and maintenance of machine learning models in production.
Key Responsibilities
Lead and mentor a team focused on delivering industry‑leading ML Ops solutions
Drive the design and implementation of scalable ML pipelines and infrastructure
Manage and maintain existing data science tools, platforms, and in‑house Python libraries
Collaborate closely with data scientists, engineers, and stakeholders to productionise models effectively
Establish and promote best practices in CI/CD, testing, monitoring, and model governance
Key Requirements
Approximately 5+ years of experience in a similar ML Ops, DevOps, or platform engineering role
Strong background in DevOps practices and/or full‑stack engineering
Proven experience leading a team, or a clear desire to step into a people management role
Hands‑on experience with containerisation technologies such as Docker and Kubernetes
Strong programming skills, ideally in Python, and experience supporting ML workflows in production
What You’ll Bring
A strategic mindset with a passion for building scalable ML systems
Strong leadership and communication skills
A collaborative approach with the ability to influence across technical teams
A drive to continuously improve processes, tooling, and team capability
Why Apply?
Opportunity to shape and lead ML Ops in a growing, innovative environment
Work on complex, real‑world problems with modern technologies
Clear progression path with leadership impact
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