Synthesia08.04.2026

Principal ML Platform Engineer

Полная занятостьУдалёнка

Обязанности

  • 01Design and improve the platform systems that support model training, evaluation, and production serving
  • 02Build infrastructure and tooling that make ML workloads more reliable, scalable, and cost-efficient
  • 03Develop internal tools and workflows that are easy to operate both by humans and by agents
  • 04Work on the architecture behind how models are deployed, served, and operated across research and product environments
  • 05Improve how we schedule, monitor, and debug workloads running on GPUs and cloud infrastructure
  • 06Develop internal tools and abstractions and agentic systems that reduce operational overhead for researchers and engineers
  • 07Drive improvements across observability, automation, reliability, and developer experience
  • 08Collaborate closely with researchers and product engineers to understand pain points and turn them into robust platform capabilities
  • 09Contribute to technical direction and make pragmatic architectural tradeoffs as the platform grows

Требования

  • 01Strong experience building or operating production systems with a focus on reliability, scalability, and maintainability
  • 02A systems mindset: you naturally think in terms of bottlenecks, failure modes, interfaces, resource usage, and long-term operability
  • 03Solid hands-on experience with cloud infrastructure, Linux, and infrastructure automation
  • 04Experience with Kubernetes and operating distributed workloads in production
  • 05Strong coding skills, ideally in Python or similar languages used for backend systems and tooling
  • 06Strong judgment around where automation adds leverage, and where human control and reliability matter most
  • 07Experience building internal platforms, developer tooling, or infrastructure abstractions used by other engineers
  • 08Comfort working in ambiguous environments and taking ownership of open-ended technical problems
  • 09A pragmatic approach: you care about solving the right problem well, not over-engineering
  • 10Operating ML infrastructure or model serving systems in production
  • 11Supporting research or data-intensive workloads
  • 12Working with GPU-based systems or other performance-sensitive infrastructure
  • 13Experience with observability and debugging in distributed systems

Условия

  • 01Hands-on IC role with significant ownership
  • 02Opportunity to shape how the ML platform evolves as the company scales
  • 03Work with cutting-edge AI video platform technology
  • 04Collaboration with top-tier researchers and product engineers
  • 05Headquarters in London with offices across Europe and the US
  • 06Recent Series E funding ($200M) with a $4B valuation