ML Platform Engineer (AI)

TL;DR

ML Platform Engineer (AI): Building and operating robust infrastructure for training, serving, and deploying generative models with an accent on reliability, scalability, and resource efficiency. Focus on developing agent-oriented internal tooling and platform abstractions to streamline workflows for research and product teams.

Location: Remote (Europe)

Company

Synthesia is the world’s leading AI video platform for business, helping organizations enhance visual communication and enterprise skill development.

What you will do

• Design and improve platform systems supporting model training, evaluation, and production serving.
• Build scalable, cost-efficient infrastructure and tooling for ML workloads.
• Develop internal tools and workflows optimized for both human and agentic operation.
• Architect systems for deploying and operating models across research and product environments.
• Improve scheduling, monitoring, and debugging of workloads on GPUs and cloud infrastructure.
• Collaborate with researchers and product engineers to translate technical pain points into robust platform capabilities.

Requirements

• Must be based in Europe
• Strong experience building or operating production systems with a focus on reliability and scalability.
• Solid hands-on experience with cloud infrastructure, Linux, and infrastructure automation.
• Experience with Kubernetes and operating distributed workloads in production.
• Strong coding skills, ideally in Python.
• Systems mindset with a focus on bottlenecks, failure modes, and resource usage.

Nice to have

• Experience operating ML infrastructure or model serving systems in production.
• Familiarity with GPU-based systems or performance-sensitive infrastructure.
• Experience with observability tools like Datadog and infrastructure-as-code like Terraform.
• Experience building agentic or LLM-powered internal tools.
• Familiarity with workflow orchestration systems such as Temporal.

Culture & Benefits

• Significant ownership in a hands-on IC role.
• Opportunity to work at the boundary of research and production engineering.
• Work in a high-growth, well-funded environment with a valuation of $4 billion.
• Collaborative culture focused on pragmatic architectural tradeoffs.