What you'll be doing

• Take a leading technical role in helping teams across Trainline adopt and operate ML and AI tooling as the technology evolves
• Support AI infrastructure, working with teams building internal platforms and customer-facing products, ensuring products are well governed, monitored, and deployed through automation
• Build and drive adoption of one standard way to deploy ML and AI products for faster onboarding and production release
• Automate the modernization of services, including fixing and preventing security vulnerabilities in libraries and dependencies
• Strengthen MLOps foundations by improving cost tracking, reducing costs, addressing security vulnerabilities, and standardizing engineering practices
• Contribute to technical strategy by evaluating options and making decisions where no established approach exists
• Communicate technical decisions clearly and help prioritize requests from ML teams
• Mentor engineers and share knowledge through documentation and enablement across the organization

Requirements

• Hands-on experience with Infrastructure as Code (IaC) and CI/CD tooling, ideally Terraform and GitHub Actions, or alternatives like AWS CloudFormation and Jenkins
• Experience with containerized workloads using Docker and cloud platforms such as AWS, GCP, or Azure
• Experience productionising AI products including agentic systems and related AIOps tooling, ideally using AWS Bedrock AgentCore or similar
• Experience with managed or self-hosted ML infrastructure such as Amazon SageMaker, feature stores (e.g. Feast), and DAG tooling (e.g. Airflow, Metaflow)
• Experience with model experiment tracking (e.g. MLflow, Weights & Biases) and monitoring tools (e.g. EvidentlyAI, CometML, Grafana, New Relic)
• Ability to write production-quality, tested Python code
• Experience leading or contributing significantly to major platform changes and migrations, with the ability to lead technical work through ambiguity
• Clear communication skills, sound prioritization, and a track record of driving adoption of shared standards and mentoring colleagues

Nice to haves

• Knowledge of cloud networking fundamentals (VPC, security groups, CDN, WAF) and identity and access management (IAM, EntraID, SSO)
• Experience with wider tech stack and partners such as Spacelift, Braintrust, and ElevenLabs

Perks and benefits

• Private healthcare and dental insurance
• Generous work from abroad policy (28 days)
• 2-for-1 share purchase plans
• EV Scheme to reduce carbon emissions
• Extra festive time off
• Excellent family-friendly benefits
• Clear career paths, transparent pay bands, personal learning budgets, and regular learning days
• Hybrid working model with minimum 60% office attendance over 12 weeks