Software Engineer
Faculty
Overview
In this role you will bring machine learning from lab to real-world impact, building scalable ML software and defining best practices. You’ll work with cross-functional teams to deliver production-grade solutions that meet client needs in national security and AI safety. You’ll influence architectural decisions and define deployment standards to ensure scalable, secure AI. This is a chance to shape responsible AI at scale for government and industry partners.
Pay / Benefits- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family-Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working
- Build and deploy production-grade ML software, tools, and infrastructure
- Create reusable, scalable ML solutions to accelerate delivery
- Collaborate with engineers, data scientists and commercial leads to solve client challenges
- Lead technical scoping and architectural decisions for feasibility and impact
- Define and implement standards for deploying ML at scale
- Act as technical advisor translating ML concepts for stakeholders
- Understanding of full ML lifecycle
- Experience operationalising models with Scikit-learn, TensorFlow, or PyTorch
- Strong Python and software engineering practices
- Hands-on experience with cloud platforms (AWS, Azure, GCP) including architecture and security
- Experience with Docker and Kubernetes
- Knowledge of core ML concepts like probability and statistics
- Excellent communicator able to guide technical and non-technical stakeholders
- Ability to work in fast-paced environment and own scope
- Excellent communication
- Cross-functional collaboration
- Autonomy and initiative
- Scikit-learn
- TensorFlow
- PyTorch
Reference: WJ-747_30176086