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    Software Engineering Intern - San Francisco, United States - Scale AI

    Scale AI
    Scale AI San Francisco, United States

    2 weeks ago

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    Description

    At Scale, we are currently expanding one of the most significant hybrid human-machine systems. Our innovative, self-regulating platform automates the training and evaluation of labelers, guaranteeing ongoing quality and efficient allocation. With an extensive network of hundreds of thousands of skilled human labelers, we handle billions of annotations every month, presenting a range of fascinating technical complexities. Our team, spanning product, systems, and infrastructure engineering, is dedicated to overcoming these challenges, driving forward AI development at an accelerated pace.

    Now taking applications for the Summer (May/June - August/September) Internship period. Join us and be part of shaping the future of AI technology

    Example Projects:

    • Ship products that allow customers to build, evaluate, and deploy generative AI applications
    • Use models to estimate the quality of tasks and labelers, and guarantee quality on requests at large scale
    • Properly route tasks from customers to labelers for low turnaround and high accuracy
    • Build methods to automatically measure, train, and optimally match labelers to tasks based on performance
    • Create optimized and efficient UI/UX tooling for Scalers to complete hundreds of complex tasks
    • Build robust machine learning models to automate requests and improve our labelers' efficiency
    • Develop new AI infrastructure products to visualize, query, and explore Scale data

    Required to have:

    • Currently pursuing a degree in a relevant field with a graduation date in Fall 2024 or Spring 2025

    Ideally you'd have:

    • Product engineering experience such as building full-stack web apps, and integrating with relevant APIs and services
    • Systems engineering experience with real-time and distributed system architecture
    • Experience building systems that process large volumes of data
    • Experience with Python, React, and/or MongoDB

    About Us:

    At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how machine learning can build innovative products. Our products provide access to human-powered data for hundreds of use cases and are used by industry leaders such as Open AI, Lyft, Meta, GM, Samsung, Airbnb, NVIDIA, and many more. We've recently raised $325 million in Series E funding at a valuation of $7B+ and are expanding our team to accelerate the development of AI applications.

    We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an affirmative action employer and inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

    We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at Please see the United States Department of Labor's Know Your Rights poster for additional information.

    We comply with the United States Department of Labor's Pay Transparency provision.

    PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

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