Transforming ML Prototypes into Scalable Production Services
Join a fully remote team within the EU to take ownership of the backend services, APIs, and infrastructure supporting machine learning models in production. This 12-month contract, with extension possibilities, offers the opportunity to work closely with Applied Scientists to turn prototypes into robust, production-ready systems.
Key Responsibilities
- Productionise ML prototypes and deploy scalable services on Kubernetes
- Build and operate APIs for real-time and batch ML inference
- Manage GPU inference workloads, autoscaling, and performance
- Own service reliability, latency, load testing, and production incidents
- Build and maintain data pipelines and production monitoring
- Collaborate with Applied Scientists to productionise new ML capabilities
Essential Skills
- Strong proficiency in Java, Kotlin, Scala, and Python
- Hands-on experience with Kubernetes, Docker, and Infrastructure as Code
- Experience building and operating production HTTP APIs
- Strong AWS experience, including IAM, S3, and CI/CD
- Experience debugging live production systems
Nice to Have
- Familiarity with Triton, TorchServe, or similar GPU inference platforms
- Experience with Kafka, Spark, or Databricks