Job description
About Us
We’re a stealth-stage deep tech startup reimagining how AI models are trained, scaled, and optimised. Our goal is to make large-scale AI systems faster, greener, more efficient, and easier to deploy. If you're excited by infrastructure that powers the bleeding edge of machine learning, we’d love to hear from you.
The Role
We're hiring a Senior Software Engineer to take the lead on building a high-performance API platform for serving machine learning models at scale. You’ll be responsible for the full infrastructure stack — from backend APIs to deployment, scaling, and performance. This is a hands-on role at the intersection of distributed systems, MLOps, and cloud-native engineering.
What You’ll Be Doing
We’re a stealth-stage deep tech startup reimagining how AI models are trained, scaled, and optimised. Our goal is to make large-scale AI systems faster, greener, more efficient, and easier to deploy. If you're excited by infrastructure that powers the bleeding edge of machine learning, we’d love to hear from you.
The Role
We're hiring a Senior Software Engineer to take the lead on building a high-performance API platform for serving machine learning models at scale. You’ll be responsible for the full infrastructure stack — from backend APIs to deployment, scaling, and performance. This is a hands-on role at the intersection of distributed systems, MLOps, and cloud-native engineering.
What You’ll Be Doing
- Architect and build scalable APIs using FastAPI (or similar), Python, and modern backend frameworks
- Design and maintain infrastructure for ML model serving
- Work closely with ML engineers to streamline training and deployment workflows
- Take full ownership of cloud infrastructure — Kubernetes, Terraform, CI/CD pipelines
- Build clean, modern dashboards and analytics tools using React or similar
- Lead on system design, performance tuning, and reliability
- 5+ years of professional software engineering experience
- Strong Python backend development skills (FastAPI or equivalent)
- Experience scaling cloud-native systems (ideally on AWS) using microservices and infrastructure-as-code
- Deep knowledge of Kubernetes and Terraform in production settings