Your new company

A forward-thinking organisation leveraging data and machine learning to drive business value at scale. With a strong emphasis on automation, security, and collaboration, the company empowers analytics teams to deliver impactful solutions across customer-facing products.

Your new role

As an ML Platform Engineer, you’ll be responsible for designing, building, and maintaining scalable machine learning infrastructure on AWS. You’ll work closely with product engineers and data scientists to streamline the ML lifecycle—from data ingestion to model deployment—ensuring agility, reliability, and security across platforms.

What you'll need to succeed

• Proven experience with AWS services (EC2, ECS, S3, Lambda, Step Functions, RDS, DynamoDB, IAM, VPC, Route 53, CloudWatch)
• Familiarity with AWS ML tools (SageMaker, AWS Glue, Amazon EMR, Airflow)
• Strong understanding of the ML lifecycle and cloud infrastructure for ML use cases
• Proficiency in Bash and Python for scripting and automation
• Experience with Infrastructure-as-Code (especially AWS CloudFormation)
• Skilled in version control (GitHub, GitHub Actions)
• Knowledge of observability tools (Grafana, Prometheus) and engineering tools (Artifactory, Snyk, Docker)
• Ability to work across the full software lifecycle
• Excellent communication skills and a commitment to inclusivity and continuous improvement

What you'll get in return

• The opportunity to work on cutting-edge ML infrastructure in a collaborative, high-impact environment
• A culture that values innovation, automation, and continuous learning
• Exposure to a wide range of AWS technologies and DevSecOps practices
• The chance to shape scalable solutions that directly influence customer experiences

What you need to do now

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.