About this role
Bridging the gap between artificial intelligence pilots and profitable enterprise deployment remains a central challenge for modern organizations, and the Global Public Sector team at Scale AI tackles this exact problem daily. Engineers on this team build custom applications, data pipelines, and evaluation infrastructure that impact millions of citizens while supporting major government and enterprise customers.
New graduates step into immediate ownership by shipping customer-facing features, engaging directly with users, and iterating rapidly on high-impact products. Successful candidates bring demonstrated product engineering capabilities, solid academic foundations in technical disciplines, and a proven history of delivering reliable software solutions at scale.
What you will do
- Own meaningful, customer-facing work from day one by shipping products and talking directly to users.
- Build reinforcement learning and post-training data pipelines to support frontier model development.
- Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers.
- Design agentic AI applications alongside observable, testable, and safe deployment tooling.
- Create advanced matching algorithms and fraud-detection systems to keep the contributor base secure.
- Construct optimized UI and UX tooling combined with machine learning algorithms for large-scale operations.
What you need
- Graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree or equivalent in Computer Science, EECS, Computer Engineering, Statistics, or a related field.
- Demonstrated product engineering experience building full-stack web applications and integrating relevant APIs.
- Previous professional experience through software engineering or product engineering internships.
- A proven track record of shipping high-quality software products and features at scale.
- Practical experience building systems capable of processing large volumes of data.
- Familiarity with programming languages and frameworks such as Python, TypeScript, React, or MongoDB.
Nice to have
- Hands-on experience with LLMs, evaluations, or agentic systems from internships, research, or personal projects
- Open source contributions or a portfolio of shipped side projects
Skills and tech stack
Questions candidates ask
Where is this position located?
Please reference the job posting's subtitle for where this position will be located. The location is listed as London, UK.
What kind of projects will I work on as a new graduate?
Example projects include building reinforcement learning and post-training data pipelines, developing evaluation infrastructure, and shipping agentic AI applications. Engineers also build fraud-detection systems and create optimized UI/UX tooling.
What is the policy for reapplying if I am not selected?
The policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows for a fair and thorough evaluation of all applicants.