Engineering
Backend Engineer
San Francisco, California
Full-time
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:
- 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 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
About Us:
At Scale, our mission is to accelerate the development of Machine Learning and AI applications across multiple markets. Our first product is a suite of APIs that allow AI teams to generate high-quality ground truth data. Our customers include OpenAI, Zoox, Lyft, Pinterest, Airbnb, nuTonomy, and many more.
Scale AI is an equal opportunity employer. We aim for every person at Scale to feel like they matter, belong, and can be their authentic selves so they can do their best work. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Scale AI is 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 EEO poster and EEO poster supplement for additional information.