Senior Software Engineer (Safety)

Overview

In this role you will lead the development and deployment of scalable, production-grade ML systems for national security and safety-focused clients. You will bridge AI research and real-world impact by architecting robust ML software and infrastructure, while guiding cross-functional teams and partnering with Frontier Labs. You will mentor engineers and shape engineering culture, ensuring secure, ethical, and high-assurance AI solutions. This role offers the chance to work on high-stakes problems with a direct influence on safety and trust in AI.

Responsibilities

• Lead technical scoping and architectural decisions for high-impact ML systems
• Design and build production-grade ML software, tools, and scalable infrastructure
• Define and implement best practices for deploying ML at scale
• Collaborate with engineers, data scientists, product managers, and commercial teams
• Act as a trusted technical advisor to customers and partners
• Mentor and develop junior engineers to strengthen the team’s depth

Key requirements

• Experience building and deploying secure, scalable LLM applications
• Operationalising models with TensorFlow or PyTorch
• Strong Python proficiency and building robust, reusable systems
• Cloud platforms experience (AWS, Azure, GCP) including architecture and security practices
• Experience with containerization and orchestration (Docker, Kubernetes)
• Ability to work autonomously in fast-paced environments
• Strong communication with technical and non-technical stakeholders

• excellent communication
• ownership and autonomy
• mentoring and coaching
• LLM applications
• AI Safety evaluation procedures
• TensorFlow

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