11 hours ago
London, United KingdomSenior
Responsibilities
- Build and deploy production-grade machine learning software, tools, and infrastructure.
- Create reusable and scalable solutions that accelerate ML system delivery.
- Collaborate with engineers, data scientists, and commercial leads to solve client 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 while translating complex ML concepts for stakeholders.
Requirements
- Understand the full machine learning lifecycle and have experience operationalising models built with Scikit-learn, TensorFlow, or PyTorch.
- Strong Python skills and solid software engineering best-practice experience.
- Hands-on experience with AWS, Azure, or GCP, including architecture and security.
- Experience using Docker and Kubernetes to build and manage applications at scale.
- Knowledge of probability, statistics, and common machine learning techniques.
- Excellent communication skills and the ability to advise non-technical stakeholders.
- Ability to work autonomously in a fast-paced environment and own scope and delivery.
Benefits
- Faculty is open to conversations about part-time hours.
- Applicants from all backgrounds are encouraged to apply.
- AI may be used for research and interview preparation, but not to generate answers during live interviews; interviews use an optional Metaview AI note-taker.
Tech Stack
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