ML Platform Engineer

About J2TT:

Jet2 Holidays is now the largest UK tour operator, flying over 17 million customers.

At Pune, we have our innovation center where we work on top notch technologies to develop products and provide services to our customers. Jet2TT is captive technology center of Jet2.

Our amazing teams work in collaboration with UK colleagues in a fast paced and agile environment to develop, innovate and leverage the latest technologies to best in class software using state-of-the-art practices.

Reporting to the ML Platform Lead, the ML Platform Engineer will be a core member of the centralised analytics platform team. In this hands-on role, you will work closely with the ML Platform Lead to build, maintain, and continuously improve secure and scalable platform capabilities that serve our Machine Learning Engineering (MLE) and Data Science community. You will own the day-to-day engineering execution of ML platform components, contributing to the reliability, observability, and operational excellence of the platform.

Key Responsibilities:

What will you do in the role
This role focuses on hands-on engineering delivery of the ML Platform, implementing standard ML patterns and contributing to platform security, scalability, and engineering excellence under the guidance of the ML Platform Lead.

Platform Engineering & Infrastructure

• Assist in building and maintaining a secure, scalable ML platform, including AWS ML foundations and LLM capabilities.

• Support the migration and ongoing management of AWS platform capabilities from MLEs into the centralised ML Platform.

• Implement ML platform technical standards and infrastructure governance practices including IAM policies, encryption, and compliance controls.

• Execute Terraform releases to the ML platform and assist in provisioning AWS accounts and Domains in coordination with the MLE team.

• Ensure shared responsibility for key infrastructure items with MLE while maintaining platform ownership standards.

• Support infrastructure provisioning, compute provisioning, auto-scaling, and managed infra downtime windows in collaboration with the Cloud Infrastructure team.

• Monitor platform availability and contribute to maintaining a strong platform security posture.

• Contribute engineering effort to wider analytics platform initiatives alongside platform specialists.

Collaboration & Processes

• Participate in the ML Platform roadmap execution by delivering against priorities defined by MLE and Data Science management through the structured intake process.

• Collaborate with MLEs to implement standard ML patterns and reusable platform components.

• Enable MLE teams through robust platform capabilities, ensuring Data Science Pods can operate independently without direct dependency on the Platform team.

• Support the intake and prioritisation process for ML platform tasks, Snowflake requests, and AWS requests originating from MLE.

• Assist in generating platform usage reports and visibility dashboards for Data Science stakeholders.

• Actively contribute to continuous improvement of data platform processes.

• Leverage cutting-edge Data Science, Machine Learning, and AI technologies to raise platform capability.

Data & Monitoring

• Own day-to-day operations and maintenance of AWS and Hex platforms in accordance with agreed ways of working.

• Manage and support feature storage infrastructure and infra-level data access controls.

• Implement and maintain comprehensive infrastructure monitoring and observability solutions.

• Work with MLEs to apply the right standards and guidance for ML practice.

• Enforce best practices for ML platform governance, compliance, and risk management, ensuring ML solutions meet regulatory standards.

Qualifications, Skills and Experience (Candidate Requirements):

· Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field with 4+ years of relevant experience in Platform Engineering, Cloud Infrastructure, or MLOps.

You will have:

• Solid understanding and hands-on experience building and managing secure, scalable ML platforms.

• Working knowledge of AWS services relevant to ML and platform foundations — SageMaker, Bedrock, Lambda, ECS/EKS, Step Functions, S3, IAM, and related services.

• Experience with infrastructure-as-code tools, specifically Terraform, for platform provisioning and releases.

• Exposure to managing and supporting Snowflake, Tableau, and Hex environments.

• Understanding of technical standards, infrastructure governance, and compliance/encryption practices.

• Good communication skills to liaise with MLEs, Data Engineers, and other technical stakeholders.

• Experience working within cross-functional and cross-regional teams, including international regions (US, UK, Europe).

• Methodical approach with strong attention to detail and a drive to continuously learn new tools, platforms, and technologies.

• Ability to operate independently on assigned tasks while escalating blockers proactively to the ML Platform Lead.