2 months ago
London, United KingdomSenior
Responsibilities
- Build and deploy production-grade machine learning software, tools, and infrastructure.
- Create reusable and scalable solutions that accelerate delivery of ML systems.
- Collaborate with engineers, data scientists, and commercial leads to solve client challenges.
- Lead technical scoping and architectural decisions for project feasibility and impact.
- Define and implement standards for deploying machine learning at scale.
- Advise customers and partners and translate complex machine learning concepts for stakeholders.
Requirements
- Experience with the full machine learning lifecycle and operationalising models built with Scikit-learn, TensorFlow, or PyTorch.
- Strong Python skills and solid software engineering best practices.
- Hands-on experience with AWS, Azure, or GCP, including architecture and security.
- Experience using Docker and Kubernetes to build and manage applications at scale.
- Understanding of probability, statistics, and common machine learning techniques.
- Strong communication skills and the ability to guide technical teams and advise non-technical stakeholders.
- Ability to work autonomously, own scope, and deliver solutions in a fast-paced environment.
Benefits
- Part-time hours may be considered.
- The interview process includes a talent team screen, pair programming interview, system design interview, and commercial interview.
Tech Stack
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