TL;DR
Software Engineer (AI Platform): Develop and maintain the AI infrastructure platform enabling production-grade machine learning products with an accent on MLOps tooling, scalable deployment, and multi-cloud integration. Focus on designing infrastructure-as-code, container orchestration, and DevSecOps processes to support distributed microservices architectures.
Location: Hybrid in London, United Kingdom
Company
Faculty is a product company specializing in human-centric AI, working with global clients across government, finance, retail, energy, life sciences, and defence since 2014.
What you will do
- Own and enhance deployment and MLOps tooling to ensure quality and reliability of software delivery.
- Develop new features for notebook environments and improve model monitoring systems.
- Collaborate with a small, fast-moving team to design and build infrastructure for delivery teams.
- Implement infrastructure-as-code and DevSecOps processes for containerized microservices.
- Integrate platform services across AWS, Azure, and GCP for global client solutions.
- Scale internal enablement capabilities to accelerate machine learning deployment.
Requirements
- Location: Must be based in or able to work hybrid in London, United Kingdom
- Strong software engineering skills in Python or Go.
- Experience with containerization and orchestration using Docker and Kubernetes.
- Proficiency in Infrastructure-as-Code tools like Terraform or CloudFormation.
- Understanding of machine learning product lifecycle and MLOps.
- Ability to work in small teams with high ownership and effective communication.
Culture & Benefits
- Unlimited annual leave policy.
- Private healthcare and dental coverage.
- Enhanced parental leave and family-friendly flexibility.
- Sanctus coaching and hybrid working model.
Hiring process
- Initial talent team screen (30 minutes).
- Pair programming interview (90 minutes).
- System design interview (90 minutes).
- Commercial interview (60 minutes).