7 hours 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 best practices and standards for deploying machine learning at scale.
- Collaborate with engineers, data scientists, product managers, and commercial teams on client challenges and opportunities.
- Act as a trusted technical advisor to customers and partners.
- Mentor junior engineers and help shape the engineering culture and technical depth.
Requirements
- Significant experience with the full ML lifecycle and operationalizing models built with TensorFlow or PyTorch.
- Deep software engineering expertise and strong Python skills focused on robust, reusable systems.
- Hands-on experience architecting and securing infrastructure on AWS, Azure, or GCP.
- Extensive experience with Docker and Kubernetes for building and managing applications at scale.
- Ability to take ownership and drive projects to completion in fast-paced, high-growth environments.
- Excellent communication skills for guiding technical teams and senior non-technical stakeholders.
Benefits
- The company is open to conversations about part-time hours.
- The interview process includes a talent team screen, pair programming interview, system design interview, and commercial interview.
- Candidates may opt out of the Metaview AI note-taker used during interviews.
Tech Stack
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