Software Engineer (Safety)

Overview

As a Software Engineer at Faculty, you will build production-grade ML software and scalable AI solutions for government and industry partners. You’ll bridge AI research and real-world impact, delivering dependable systems while collaborating with cross-functional teams and Frontier Labs. You will set technical standards for deploying ML at scale and advise clients on complex ML concepts. This role offers opportunities to shape responsible AI across high-stakes missions and advance safety-focused innovation.

Responsibilities

• Build and deploy production-grade ML software, tools, and infrastructure
• Create reusable, scalable ML solutions and test Frontier AI models
• 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 translating ML concepts for stakeholders

Key requirements

• Experience with building LLM applications
• Strong Python skills and software engineering practices
• Hands-on with cloud platforms (AWS, Azure, GCP) including architecture and security
• Experience with Docker and Kubernetes for scalable applications
• Solid understanding of core ML concepts and lifecycle
• Experience with frameworks like Scikit-learn, TensorFlow, or PyTorch
• Excellent communicator able to guide technical teams and advise non-technical stakeholders
• Enjoys fast-paced environments and ownership of scope and delivery
• excellent communicator
• ability to guide technical teams
• stakeholder management
• Python
• LLM applications
• multi-agent harness tooling

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