PBT Group is seeking a skilled Machine Learning Engineer with strong Google Cloud Platform (GCP) and Vertex AI experience to join a high-performing data and AI delivery team.

This role is ideal for an engineer passionate about designing, deploying, and operationalising machine learning solutions within modern cloud environments. The successful candidate will work closely with Data Scientists, Data Engineers, Analysts, and business stakeholders to build scalable ML pipelines and production-ready AI solutions.

The environment is highly collaborative and delivery-focused, with exposure to enterprise-scale data and AI transformation initiatives.

Key Responsibilities

Machine Learning Engineering

• Design, develop, deploy, and maintain scalable machine learning solutions on GCP.
• Build and operationalise ML models using Vertex AI.
• Develop and manage end-to-end ML pipelines and workflows.
• Support model training, evaluation, deployment, monitoring, and optimisation.
• Collaborate with Data Scientists to productionise machine learning models.

Cloud & Data Engineering

• Integrate ML solutions with cloud-based data platforms and pipelines.
• Work with structured and unstructured datasets at scale.
• Develop feature engineering and model-serving capabilities.
• Ensure data quality, model reliability, and performance optimisation.

MLOps & Automation

• Implement CI/CD and MLOps best practices for ML deployment and lifecycle management.
• Automate model retraining, monitoring, and performance tracking.
• Support model governance, versioning, and reproducibility.
• Monitor production ML environments and troubleshoot issues proactively.

Collaboration & Delivery

• Work closely with business and technical stakeholders to understand AI and analytics requirements.
• Participate in Agile delivery ceremonies and contribute toward sprint commitments.
• Maintain clear technical documentation and implementation standards.
• Stay up to date with emerging AI, ML, and cloud engineering trends.

Required Skills & Experience

Essential

• 3–6 years’ experience in Machine Learning Engineering or AI Engineering roles.
• Strong hands-on experience with:
  • Vertex AI
  • Google Cloud Platform (GCP)
  • Python
  • SQL
• Experience deploying and operationalising ML models in production environments.
• Solid understanding of machine learning workflows and model lifecycle management.
• Experience building ML pipelines and automation processes.
• Exposure to cloud-native data and AI architectures.
• Strong problem-solving and analytical skills.

Advantageous

• Experience with:
  • BigQuery
  • Dataflow
  • Kubernetes
  • Docker
  • Terraform
• Exposure to MLOps frameworks and CI/CD pipelines.
• Experience with Generative AI / LLM integrations.
• Financial services or enterprise consulting exposure.

Ideal Candidate Profile

We are looking for someone who:

• Enjoys building scalable, production-ready AI solutions.
• Is passionate about modern cloud and ML engineering practices.
• Can bridge the gap between Data Science and Engineering.
• Works well in collaborative Agile delivery environments.
• Has strong communication and stakeholder engagement capability.

Key Competencies

• Strong analytical and technical problem-solving skills.
• Delivery-focused mindset.
• Ability to work independently and within teams.
• Strong communication and collaboration ability.
• Adaptability and continuous learning mindset.

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