Applied AI Software Engineer, International Public Sector
Scale is growing rapidly, and joining the Global International Public Sector team is an opportunity to work on one of the most rapidly expanding teams at Scale. This team is responsible for generating, executing, and fostering Scale’s work outside of the United States. There are three core types of work involved:
- Building custom LLMs
- Providing high-quality training data for research institutions building LLMs from scratch
- Partnerships, upskilling, and advisory
Scale is looking for an Applied AI Software Engineer to lead the integration of Generative AI into customer services. You will engage with customers to understand their AI needs, design and execute modeling experiments using LLMs and RAG, and develop robust, production-grade services. Key responsibilities include building end-to-end AI systems, optimizing performance through data-driven experiments, and designing evaluation strategies. Ideal candidates will have experience as Forward Deployed Engineers, CTOs, or Founding Engineers at startups, and a passion for shaping the future of data-centric AI. If this describes you, we encourage you to apply!
You will:
- Scope and implement AI-driven solutions to ambiguous customer problems
- Build end-to-end AI systems using Scale’s Generative AI Platform
- Build automated frameworks to ingest and query large amounts of unstructured data
- Work cross functionally with our data annotation teams, and fine tune LLMs using this data
- Build evaluation systems that leverage human experts and automated approaches
- Travel up to 2 weeks every 2 months to meet with the customer
Minimum Qualifications:
- Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
- 2+ years of engineering experience, post-graduation
- Strong coder with demonstrated proficiency in programming languages such as Python, Java, C++, TypeScript/JavaScript, or similar
- Ability and interest in traveling to the client site in the Middle East region at least one week every 2 months
Ideal Qualifications:
- Proficient in reading and writing in Arabic
- Past experience working at a startup or in a forward-deployed role
- Has experience working cross functionally with operations
- Have experience building solutions with LLMs and a deep understanding of the overall Gen AI landscape
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
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 organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We 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 accommodations@scale.com. 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.
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