Platform Engineer

Scale is powering this generative AI wave by providing the data and infrastructure for companies to build large-scale foundation models. AI is rapidly changing the world, and Scale is growing to meet that rapid demand. Our customers include OpenAI, Microsoft, Adept, Stability AI and many more major players in this space!

The Platform team is responsible for building the core abstractions and infrastructure on which the products can be built and iterated rapidly. The team owns how data flows throughout the scale platform. We’re looking for people with a strong background or interest in building distributed systems, data-intensive applications, and machine learning infrastructure. You have a growth mindset and are comfortable learning new technologies.

You will:

Build engineering foundations for Scale, such as machine learning infrastructure, data platform, APIs framework and task dispatching systems

Collaborate with stakeholders across the organization, such as production engineers, machine learning scientists, customer operations, etc.

Own services or systems and define their long-term health goals, while also improving the health of surrounding components

Mentor other engineers and become deeply involved in design and code review

Improve our high engineering standards, tooling, and process

Work directly with our engineering and sales teams to create backend and infrastructure solutions to meet their challenging data and security needs

Work with our Security Team on security compliance, pen tests and mitigations that improve security across Scale

Build systems capable of handling millions of frames of data every day, making it available to both our workforce and our internal teams with high availability

Ideally you'd have:

2-7 years of industry experience as a software engineer post graduation

Systems engineering experience with real-time and distributed system architecture

Experience building systems that process large volumes of data

Experience in using the following systems in production: AWS, Typescript, Node, MongoDB, MLflow, Python (note that we are mostly language-agnostic and are open to using whatever is the best tech for the problem at hand)

Experience working with Docker, Kubernetes, and Infrastructure as code (eg terraform); bonus points for running GPU/ML workloads

Nice to haves:

Prior startup experience to help us grow responsibly

Experience with core AWS technologies such as VPC, EC2, ALB, ASG, Spot Instances

Experience in operating or managing Infrastructure such as Spark, Presto, Hive

Mentored and grown members of your team or been a tech lead on large projects

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 . 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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