6 months 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, commercial leads, clients, and partners 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 ML concepts for stakeholders.
Requirements
- Understand the full machine learning lifecycle and have experience operationalizing models built with Scikit-learn, TensorFlow, or PyTorch.
- Demonstrate strong Python skills and solid software engineering best-practice experience.
- Have hands-on experience with AWS, Azure, or GCP, including cloud architecture and security.
- Have experience using Docker and Kubernetes to build and manage applications at scale.
- Understand probability, statistics, and common machine learning techniques.
- Communicate effectively with technical teams and non-technical stakeholders.
- Be comfortable owning scope and independently solving and delivering solutions.
Benefits
- Part-time hours may be possible.
- The interview process includes a talent team screen, pair programming interview, system design interview, and commercial interview.
- Candidates may opt out of the AI note-taker used during interviews.
Tech Stack
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