Principal ML Platform Engineer
Synthesia is an active London-based enterprise AI video platform that lets businesses create, localize, manage, and publish videos using AI avatars and voiceovers.
Funding history
About Synthesia
Synthesia Limited provides browser-based AI video creation for business communications, training, sales enablement, marketing, and support. Its platform includes AI-assisted creation, avatars, voiceovers, translation/localization, collaboration, and publishing workflows.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and improve systems for model training, evaluation, serving, and deployment. You will build reliable, scalable, cost-efficient infrastructure and internal tools; improve GPU and cloud workload scheduling, monitoring, and debugging; reduce operational overhead through automation and agentic systems; and make architectural trade-offs with researchers and product engineers.
Requirements
- Experience building or operating reliable, scalable, and maintainable production systems
- Systems thinking for bottlenecks, failure modes, interfaces, resource usage, and operability
- Experience with cloud infrastructure, Linux, and infrastructure automation
- Experience with Kubernetes and distributed production workloads
- Strong coding skills in Python or similar backend and tooling languages
- Experience building internal platforms, developer tooling, or infrastructure abstractions
- Ability to take ownership of ambiguous technical problems
Responsibilities
- Design and improve systems for model training, evaluation, and production serving
- Build reliable, scalable, and cost-efficient ML infrastructure and tooling
- Develop internal tools and workflows for humans and agents
- Design architecture for model deployment, serving, and operations
- Improve GPU and cloud workload scheduling, monitoring, and debugging
- Develop agentic systems that reduce operational overhead
- Improve observability, automation, reliability, and developer experience
- Collaborate with researchers and product engineers on platform capabilities
- Contribute technical direction and architectural trade-offs