Software Engineer

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

Responsibilities

• 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

Key requirements

• 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

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