Machine Learning Platform Engineer (Remote - Europe)

Machine Learning Platform Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Platform Engineer in Europe.

We are seeking a talented Machine Learning Platform Engineer to support the infrastructure and operational needs of AI-driven systems. In this role, you will collaborate closely with AI researchers, engineers, and product teams to deploy, manage, and optimize cloud-based machine learning workloads. You will design scalable, reliable infrastructure, implement CI/CD pipelines, and maintain observability for production systems. The ideal candidate combines hands-on expertise in Kubernetes, AWS, Infrastructure-as-Code, and workflow orchestration with a proactive, problem-solving mindset. This role offers the opportunity to work in a fast-growing AI environment, influence platform architecture, and directly contribute to delivering innovative AI-powered solutions at scale.

Accountabilities

• Deploy, manage, and optimize machine learning models and data pipelines on Kubernetes (EKS) and cloud infrastructure
• Collaborate with AI researchers to support infrastructure requirements and facilitate research-to-production workflows
• Implement and maintain Infrastructure-as-Code (Terraform/Terragrunt) for provisioning and scaling cloud resources
• Build and manage CI/CD pipelines to automate model and application deployment
• Monitor, troubleshoot, and enhance system performance using observability tools (e.g., Datadog)
• Manage workflow orchestration platforms (e.g., Temporal.io) to streamline model and data lifecycles
• Partner with finance and operations teams to integrate cost management and vendor oversight (FinOps)

Requirements

Proven experience with cloud-based hosting, preferably AWS, and container orchestration platforms like Kubernetes (EKS)
Strong knowledge of Infrastructure-as-Code frameworks such as Terraform and Terragrunt
Experience building and managing CI/CD pipelines and deployment workflows
Proficiency with scripting languages such as Python and operational support of production systems
Familiarity with observability and monitoring platforms (e.g., Datadog) for large-scale infrastructure
Ability to work collaboratively with AI researchers and engineering teams in an asynchronous, remote-first environment
Strong problem-solving skills, adaptability in dynamic environments, and attention to detail
Preferred: experience with high-volume SaaS products, workflow orchestration platforms (Temporal.io), and frontend or full-stack application support

Benefits

• Competitive base salary starting at EUR/GBP/CHF 100,000 + stock options
• Fully remote role within the EU, UK, or Switzerland with flexible work arrangements
• 25 days of leave plus local holidays
• Opportunity to work on cutting-edge AI and machine learning infrastructure
• Collaborative, fast-paced, and growth-oriented work environment
• Exposure to proprietary AI technology and direct collaboration with world-class AI researchers

Jobgether - Talent Matching Platform

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

📊 It compares your profile to the job's core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.

Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!