Platform Engineer (ML Platform)

Job Description

DTG Global is partnering with a scaling SaaS company building a robust machine learning platform to power their product offerings. They are looking for a Platform Engineer to help build and maintain the infrastructure that enables their data science and ML teams to deploy and scale models efficiently.

This is a team that values reliability, automation and clean systems design, where you will work at the intersection of ML, infrastructure and product.

What you’ll be doing

• Building and maintaining scalable infrastructure to support the deployment and monitoring of ML models
• Developing and managing Kubernetes-based environments for model serving and orchestration
• Automating workflows for data processing, training and model deployment
• Working closely with data science and engineering teams to translate ML needs into stable platform solutions
• Implementing observability and monitoring tools to ensure system health and performance

What we’re looking for

• Strong background in platform engineering, DevOps or infrastructure with an interest in supporting ML workflows
• Experience with containerisation and orchestration (Docker, Kubernetes)
• Proficiency with infrastructure-as-code tools (Terraform, CloudFormation)
• Familiarity with cloud platforms (AWS, GCP or Azure)
• Understanding of CI/CD pipelines and automation best practices

Nice to have

• Exposure to ML platform tools (Kubeflow, MLflow, Seldon, SageMaker)
• Experience supporting data pipelines and distributed systems (Airflow, Spark)
• Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK stack)
• Previous experience working in a scaling SaaS or product-led environment

Why this role

• Shape the infrastructure of a scaling ML platform used in production
• Work with a team that values clean engineering and automation
• Flexible hybrid and remote working options
• Competitive salary, equity and benefits package

If you’re looking to apply your platform engineering skills in a team that values technical excellence while working at the intersection of ML and infrastructure, we’d love to hear from you.

Apply now or contact us for a confidential discussion.