Description
Faculty is seeking a Machine Learning Engineer to deliver bespoke AI solutions for clients. The engineer will build scalable machine learning systems, partnering with clients and teams to ensure seamless delivery and technical feasibility.
The National Security and AI Safety business unit focuses on advancing responsible AI development and deployment for national security and global stability. The ideal candidate will have experience with LLM applications, multi-agent harness tooling, and AI Safety evaluation procedures.
Responsibilities:
- Building and deploying production-grade ML software, tools, and infrastructure
- Creating reusable solutions that accelerate ML system delivery and capability testing
- Collaborating with engineers, data scientists, and commercial leads to solve client challenges
- Leading technical scoping and architectural decisions
- Defining and implementing standards for deploying machine learning at scale
- Acting as a technical advisor to customers and partners
Requirements:
- Experience with LLM applications and AI Safety evaluation procedures
- Strong Python skills and software engineering best practices
- Hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP)
- Familiarity with container and orchestration tools (e.g., Docker, Kubernetes)
- Understanding of core ML concepts and the full machine learning lifecycle
- Excellent communication skills
Benefits:
- Opportunity to work on high-impact projects
- Collaborative and dynamic work environment
- Growing company with a strong reputation
Interview Process:
- Talent Team Screen (30 minutes)
- Pair Programming Interview (90 minutes)
- System Design Interview (90 minutes)
- Commercial Interview (60 minutes)