About this role
Engineers who thrive on direct customer interaction and rapid product iteration will find an ideal home at Scale AI. New graduates stepping into this environment take ownership of customer-facing products immediately, bridging the gap between raw machine learning models and enterprise-grade applications. The team builds the data pipelines, evaluation frameworks, and agentic tools that help global organizations move AI initiatives from pilot phases into production.
Daily responsibilities span a wide array of technical challenges, from developing fraud-detection systems to creating optimized UI and UX tooling for a massive contributor base. Success in the role requires a bias for action, comfort with large-scale data systems, and an eagerness to collaborate closely with users to determine what features need to be built next.
What you will do
- 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.
- Ship agentic AI applications alongside the tooling required to make them observable, testable, and safe to deploy.
- Create optimized and efficient UI/UX tooling combined with machine learning algorithms for over one hundred thousand contributors.
- Design advanced matching algorithms that pair contributors with customers to maximize turnaround time and accuracy.
- Construct fraud-detection systems that remove bad actors and maintain a trusted contributor network.
What you need
- Graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree or equivalent in a relevant technical field such as Computer Science, EECS, Computer Engineering, or Statistics.
- Demonstrated product engineering experience building full-stack web applications and integrating with relevant APIs.
- Prior software or product engineering internship experience.
- A proven track record of shipping high-quality products and features at scale.
- Hands-on experience building systems that process large volumes of data.
- Working familiarity with Python, TypeScript, React, and/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
Benefits
- Comprehensive health, dental and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend
Skills and tech stack
Questions candidates ask
What is the base salary range for the role?
The base salary range for this full-time position located in San Francisco is $124,000 to $162,000 USD. Additional compensation may include equity subject to Board of Director approval.
What qualifications are required for graduation timelines?
Applicants must have a graduation date in Fall 2026 or Spring 2027. Candidates should be pursuing a Bachelor's degree or equivalent in a relevant field like Computer Science, EECS, Computer Engineering, or Statistics.
Can I reapply if I am not selected?
Scale AI has a policy requiring a 90-day waiting period before reconsidering candidates for the same role. This ensures a fair and thorough evaluation process for every applicant.
What types of projects will I work on?
Engineers work on building reinforcement learning pipelines, evaluation infrastructure for model reliability, agentic AI applications, and optimized UI tooling for platform contributors. Projects also include developing fraud-detection systems and data visualization tools.