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Scale AI

Supplies AI training data and builds AI apps

Senior Software Engineer - Platform

Platform EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 5 years of full-time software engineering experience, focused on backend, infrastructure, and distributed systems.
  • Experience building and operating production systems with strong reliability, availability, and scale requirements.
  • Deep familiarity with workflow orchestration platforms such as Temporal, Cadence, AWS Step Functions, Kubernetes, or similar systems.
  • Deep familiarity with Kubernetes and containerized production environments, and familiarity with Terraform and Docker.
  • Strong knowledge of distributed-systems concepts, including asynchronous execution, retries, idempotency, fault tolerance, state management, and observability.
  • A track record of leading technically complex projects from design through rollout and ongoing operation.
  • Ability to collaborate effectively with platform consumers and non-technical stakeholders.

Responsibilities

  • Lead the architecture, design, implementation, and operation of the core orchestration platform.
  • Build durable workflow infrastructure using technologies such as Temporal, Cadence, Kubernetes, and cloud-native systems.
  • Define platform primitives and APIs for scheduling, retries, state management, task execution, observability, and workflow lifecycle management.
  • Partner with product, infrastructure, data, and application teams to understand workflow needs and turn them into reusable platform capabilities.
  • Improve the reliability, scalability, security, and developer experience of services that run critical company workflows.
  • Establish technical standards and best practices for distributed workflow development, deployment, testing, and incident response.
  • Drive cross-functional technical decisions and communicate platform direction clearly to engineers and stakeholders.

Desired Qualifications

  • Experience with data warehouses such as Snowflake and Firebolt, and data pipeline/ETL tools such as Dagster and dbt.
  • Experience with authentication and authorization systems such as Zanzibar and Authz.
  • Experience scaling products at hyper-growth startups.
  • Interest in working with AI technologies.

About the Company

Scale AI

Supplies AI training data and builds AI apps

Scale AI supplies the data that AI labs use to train and test their models, and it builds custom AI applications for companies and government agencies such as the Pentagon. It first made its name labeling camera and sensor data for self-driving car companies like Waymo, then worked with OpenAI on InstructGPT, the 2022 forerunner of ChatGPT. Freelancers, some of them doctors and lawyers, write, label, and grade examples through its Outlier platform, and labs pay Scale for this data and for tests of model quality. Clients pay Scale to build AI tools on their own data, and some of those tools run on classified military networks. Alexandr Wang and Lucy Guo founded Scale AI in 2016, and it is based in San Francisco.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$1.6B
Headquarters
San Francisco, CA
Founded
2016

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