6 months ago
London, United KingdomSenior
Responsibilities
- Lead technical scoping and architectural decisions for high-impact machine learning systems.
- Design and build production-grade ML software, tools, and scalable infrastructure.
- Define and implement standards and best practices for deploying machine learning at scale.
- Collaborate with engineers, data scientists, product managers, and commercial teams to solve client challenges.
- Advise customers and partners by translating complex technical concepts into actionable strategies.
- Mentor junior engineers and help shape the engineering culture and technical depth of the team.
Requirements
- Significant experience across the full machine learning lifecycle, including operationalising models built with TensorFlow or PyTorch.
- Deep software engineering expertise and strong Python skills focused on robust, reusable systems.
- Hands-on experience architecting cloud infrastructure with AWS, Azure, or GCP, including security considerations.
- Extensive experience using Docker and Kubernetes to build and manage applications at scale.
- Strong ownership, autonomy, communication, and stakeholder-guidance skills in fast-paced environments.
Benefits
- The company is open to conversations about part-time hours.
- The interview process consists of a 30-minute talent screen, 90-minute pair programming interview, 90-minute system design interview, and 60-minute commercial interview.
Tech Stack
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