Forward Deployed Engineer

As a Machine Learning Engineer at Faculty, you’ll bring ML from lab to production, shaping scalable software and best practices. You’ll work across cross-functional teams and with government clients to deliver high-impact, production-grade ML systems. You’ll influence architectural decisions and standards, ensuring secure and trustworthy AI at scale. This role offers the chance to contribute to national security initiatives and responsible AI deployment at pace.

• 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 a technical advisor to customers and partners, translating complex ML concepts for stakeholders

• Experience with end-to-end ML lifecycle and operationalising models using Scikit-learn, TensorFlow, or PyTorch
• Strong Python programming skills and software engineering practices
• Hands-on experience with cloud platforms (AWS, Azure, GCP) including architecture and security
• Experience with Docker and Kubernetes for scalable applications
• Solid understanding of core ML concepts (probability, statistics, common learning techniques)
• Excellent communication and ability to advise non-technical stakeholders
• Thrives in a fast-paced environment with autonomous scope ownership

• Excellent communicator
• Collaborative cross-functional teamwork
• Autonomy and initiative
• ML lifecycle operationalisation
• Python software engineering
• Cloud platforms (AWS, Azure, GCP)