Infrastructure Engineer
Infrastructure/Platform Engineer owning Neuphonic's cloud infrastructure and voice-AI inference systems: building and scaling production on GCP with Kubernetes, Docker and Terraform, optimising GPU inference performance, latency and cost, plus CI/CD, monitoring and incident response. Must be based in Australia or NZ for production support complementing UK/India teams.
- Compensation
- Not disclosed
- Location
- London
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Devops
- Posted
Skills
Must have
- Strong experience building and operating production cloud infrastructure at scale
- Hands-on experience with GCP, Kubernetes, Docker, Terraform, and Python
- Experience with CI/CD, monitoring, observability, and production incident response
- Strong understanding of infrastructure performance, scalability, and cost optimisation
- Experience participating in on-call rotations or taking responsibility for production incidents
- Proactive approach: identifying bottlenecks, experimenting with improvements, optimising production systems
- Comfortable working autonomously, making architectural decisions, and taking ownership of critical systems
- Based in Australia or New Zealand and comfortable providing production support during agreed hours complementing UK and India teams
Nice to have
- Experience with AI/ML inference, GPU infrastructure, or vLLM
- Experience hosting audio, speech, or real-time AI applications
- Experience with C++
- Familiarity with SOC 2, ISO 27001, or other security compliance frameworks
- Experience with private cloud or on-premise enterprise deployments
Full description
About Neuphonic
Neuphonic is building the next generation of voice AI, making natural, real-time speech accessible across devices, languages, and applications.
Our technology enables ultra-low-latency text-to-speech, voice cloning, and multilingual speech generation. We're pushing the boundaries of what's possible with speech models, from high-performance cloud inference to running AI directly on everyday devices without expensive GPUs or an internet connection.
We're a small, ambitious team of researchers and engineers building technology used by developers and businesses around the world. Our open-source releases have reached millions of downloads, and we're growing quickly.
Why we're hiring
As our customer base grows, we need to scale our production infrastructure while maintaining the performance, reliability, and low latency that our products depend on.
We're looking for an Infrastructure / Platform Engineer to take ownership of our cloud infrastructure and inference systems. You'll work closely with our engineering and ML teams to build scalable, reliable, and cost-efficient systems.
A key part of this role is extending our production support coverage beyond UK working hours. We're hiring in Australia or New Zealand to help us work towards 24/7 support for our production customers, so we're looking for someone comfortable taking ownership of live systems, responding to incidents, and making independent technical decisions.
Importantly, this isn't just about keeping our systems running. We want someone who will actively look for ways to improve how we build, deploy, and serve our models, continually experimenting, optimising, and evolving our infrastructure as we scale.
What you'll own
- Cloud infrastructure: Build, manage, and scale our production infrastructure across GCP and GPU cloud providers using Kubernetes, Docker, and Terraform.
- Inference optimisation: Continuously improve inference performance, latency, throughput, GPU utilisation, and infrastructure costs through profiling, experimentation, and iteration, rather than simply maintaining the status quo.
- Platform evolution: Identify bottlenecks and inefficiencies in how we build, deploy, and serve models, and take ownership of implementing improvements.
- Production reliability: Monitor critical systems, respond to incidents, and help ensure reliable service for our customers outside UK working hours.
- Infrastructure architecture: Make autonomous technical decisions that balance scalability, reliability, performance, and cost.