Requirements

A degree in a STEM field or equivalent
A solid foundation in computer science principles
Proven track record designing and operating scalable backend systems in production environments
Deep proficiency in Python as your primary language, with solid command of additional programming languages
Expertise in distributed systems and modern infrastructure practices like containerisation and orchestration
Hands-on experience addressing challenges across the AI/ML lifecycle, including deployment, orchestration, and model management

Nice to have

Experience with Infrastructure as Code (IaC) tools like Terraform or Ansible
Familiarity with frameworks for high-performance model serving, especially for large-scale or Generative AI models
Experience building internal platforms or developer tools
Experience integrating third-party APIs and services to build resilient, production-grade solutions
Knowledge of data and model versioning strategies and tools
Side projects or contributions to open-source projects

Designing, building, and maintaining scalable services that support the AI lifecycle
Developing infrastructure and APIs that integrate third-party services and grow with the business
Implementing and managing robust CI/CD pipelines to validate, deploy, and monitor a diverse range of models
Building and scaling APIs and SDKs for serving AI models and systems
Ensuring low latency and high availability to meet business needs
Partnering with product teams to design and deliver accessible AI solutions
Building frameworks to track data drift, model decay, and operational health
Establishing the backbone for AI governance and reproducibility
Versioning data and models and managing a central feature store
Tracking lineage to ensure a clear, auditable path from research to production

*Final compensation will be determined based on the candidate's qualifications, skills, and previous experience