- San Francisco
- Date Posted
- Jun. 2, 2021
- Software Engineering
Scale is building out one of the largest hybrid human-machine systems. Scale’s self-regulating system automatically trains workers and ensures continuous quality and optimal allocation. We have thousands of human labelers that complete millions of tasks a month, and that comes with a host of interesting technical challenges. From product to systems to infrastructure engineering, we’re tackling it all to accelerate the development of AI.
The Infrastructure 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 be:
- Creating, building, educating, training and designing cloud computing architectures for our customers and internal teams
- Work directly with our engineering and sales teams to create backend and infrastructure solutions to meet their challenging data and security needs.
- Create abstractions of our core infrastructure which can scale to millions of humans and ML models working together.
- Propose, design, build, and deploy security improvements across Scale’s environments.
- Work with our advisors and third party vendors and auditors on security compliance, pen tests and mitigations.
- 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.
This role could be a fit if you have:
- 1+ 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 or interest in using the following: AWS, Typescript, Node, Mongo, MLflow, Spark, Presto, Python (note that we are mostly language-agnostic and are open to using whatever is the best tech for the problem at hand)
- At least a Bachelor’s degree (or equivalent) in a relevant field.
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
- Experience working with Docker, Kubernetes, and Infrastructure as code (eg terraform); especially for running GPU/ML workloads
- Mentored and grown members of your team or been a tech lead on large projects
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, 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 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 firstname.lastname@example.org. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.