19 days ago
London, United KingdomMid Level
Responsibilities
- Build and deploy production-grade machine learning software, tools, and infrastructure.
- Create reusable and scalable solutions for delivering ML systems and testing frontier AI models.
- Collaborate with engineers, data scientists, commercial leads, clients, and partners to solve critical challenges.
- Lead technical scoping and architectural decisions to ensure project feasibility and impact.
- Define and implement standards for deploying machine learning at scale.
- Advise customers and partners by translating complex ML concepts for technical and non-technical stakeholders.
Requirements
- Comfort building LLM applications and familiarity with multi-agent harness tooling and AI safety evaluation procedures.
- Strong Python skills and solid software engineering best practices.
- Hands-on experience with cloud platforms and infrastructure such as AWS, Azure, or GCP, including architecture and security.
- Experience with Docker and Kubernetes for building and managing applications at scale.
- Understanding of probability, statistics, and common machine learning techniques.
- Experience across the full machine learning lifecycle and operationalizing models built with Scikit-learn, TensorFlow, or PyTorch.
- Strong communication skills and ability to guide technical teams and advise non-technical stakeholders.
- Ability to work autonomously in a fast-paced environment and own delivery solutions.
Tech Stack
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