Lead ML Engineer

Gazelle Global Consulting Limited; Bradford-on-Avon; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Gazelle Global Consulting Limited is seeking a Lead ML Engineer in Bradford for a 12-month hybrid contract. You will help build and mature the deployment environment for a range of enterprise machine learning models, collaborating with architecture, data science and process innovation teams to productionise ML at scale.

You will focus on strengthening deployment maturity, building robust ML pipelines and supporting monitoring and operation of models across predictive, text-embedding and

Qualifications

• Experience deploying ML models in production environments.
• Strong Python development skills and data preprocessing expertise.
• Familiarity with Kubeflow/TFX and Vertex AI orchestration on GCP.
• Ability to build robust ML pipelines, monitoring, and opti msation.
• Experience with CI/CD/CT pipelines for ML models and MLOps.

Responsibilities

• Lead the development of the deployment environment for enterprise ML models.
• Mature deployment pipelines and support monitoring across use cases.
• Collaborate with architecture, data science and process teams to productionise ML at scale.

Skills

Python development

ML deployment

Model monitoring

CI/CD for ML

A/B testing

Data preprocessing

Pipelines

MLOps

Containerization

GCP

Tools

Kubeflow

TFX

Vertex AI

Cloud Platform (GCP)

Container Registry

Artifact Registry

Pylint

Job description

We're looking for a Lead ML Engineer to help build and mature the deployment environment for a range of enterprise machine learning models. Based in Bradford, this 12-month hybrid contract offers the opportunity to work closely with architecture, data science and process innovation teams on productionising ML at scale.

You'll focus on strengthening deployment maturity, building robust ML pipelines and supporting the monitoring and operation of models across predictive, text-embedding and foundation model use cases.

Key Skills:

• Kubeflow and TFX with Vertex AI as the orchestration layer
• Strong Python development
• GCP and ML model deployment
• Data preprocessing, optimisation, training and serialisation
• Model A/B testing and monitoring
• CI/CD/CT for ML models
• Container Registry and Artifact Registry
• Pylint, code coverage and static code analysis
• Continuous Machine Learning (CML)