10 hours ago
London, United KingdomStaff+
Responsibilities
- Steer technical strategy, system architecture, and capability testing for complex ML systems and frontier AI models.
- Architect production-grade secure ML software, orchestration tools, and scalable cloud infrastructure.
- Establish standards for safe, reliable, ethical, and scalable machine learning deployment.
- Translate client needs into resilient AI solutions with cross-functional teams and executive stakeholders.
- Advise senior clients and partners as an AI safety and technical authority.
- Mentor engineering talent and elevate team capabilities.
- Advance safety evaluation procedures, multi-agent harness tooling, and AI governance frameworks with Frontier Labs.
Requirements
- Significant leadership experience designing, deploying, and securing scalable LLM applications, multi-agent frameworks, and AI safety evaluation processes.
- Exceptional software engineering fundamentals and advanced Python expertise.
- Deep hands-on experience with AWS, Azure, or GCP; Docker and Kubernetes; scalable cloud architectures; agent sandboxing; and end-to-end cybersecurity.
- Mastery of the full ML lifecycle and proven experience operationalising production systems with PyTorch, TensorFlow, or similar frameworks.
- Strategic ownership, autonomy, and experience guiding technical decisions in fast-paced, high-growth environments.
- Strong communication skills with technical teams and senior non-technical stakeholders.
Benefits
- Part-time hours may be available.
- The company supports an inclusive and diverse workplace and encourages applications from people of all backgrounds.
Tech Stack
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