26 days 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, commercial leads, customers, and partners to solve critical client challenges.
- Lead technical scoping and architectural decisions to assess project feasibility and impact.
- Define and implement standards for deploying machine learning at scale.
- Act as a technical advisor and translate complex ML concepts for technical and non-technical 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-practices experience.
- Hands-on experience with cloud platforms and infrastructure such as 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.
- Excellent communication skills and the ability to advise technical teams and non-technical stakeholders.
- Ability to work autonomously in a fast-paced environment and own scope, problem-solving, and delivery.
- Eligibility for UK Developed Vetting may be required because of government client work.
Benefits
- Occasional onsite work with clients may be required.
- Part-time hours are open for discussion.
- The interview process includes a talent team screen, pair programming interview, system design interview, and commercial interview.
Tech Stack
Categories
Forward Deployed
