Labelbox

Senior Backend Engineer, Platform

San Francisco, CA
USD 170k - 225k
Kubernetes Kotlin React Microservices Elasticsearch TypeScript API Azure AWS Python Kafka JavaScript GCP Streaming
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Description

Labelbox is the data factory for generative AI, providing the highest quality training data for frontier and task-specific models. Labelbox’s comprehensive platform combines on-demand labeling services with the industry-leading data labeling platform. The Boost labeling service is powered by the Alignerr community of highly-educated experts, who span all major languages and a diverse range of advanced subjects. They are available on-demand to rapidly generate new data for supervised fine-tuning, RLHF, and more. Labelbox’s software-first approach delivers unmatched control and transparency into the labeling process, leading to the generation of high-quality, consistent data at scale.

Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.



About the Role

Join our team of world-class engineers and build the next generation of AI products!

As a Senior Backend Engineer in the Platform team, in this specific role, you'll be leading the development of various aspects of our core services around identity and access management (IAM). 

More specifically, this role within our Platform team will help drive the evolution of our IAM capabilities so that Labelbox’s customers can ensure that the AI models that they are developing on Labelbox are secure from unauthorized access, harm, or disruption.

Your Day to Day

  • Design, Develop, and Deploy: Own the design, development, and deployment of critical backend systems for enterprise-grade security, including role-based access, authentication, and authorization.
  • Scalability and Performance: Architect and implement highly scalable, secure, and performant systems that handle billions of records at blazing-fast speeds.
  • Customer Collaboration: Work closely with our customers to understand their issues, troubleshoot them, and use their feedback to continuously improve our platform.
  • Project Leadership: Lead initiatives from concept to execution, collaborating across teams to bring your vision to life, and act as a project owner.
  • Strategic Planning: Shape our company's future by defining the Platform team’s IAM roadmap and working hand-in-hand with senior leadership.
  • Innovation in AI: Play a key role in building new capabilities for an AI platform used by leading AI labs for developing powerful multi-modal large language models (LLMs).

About You

  • 6-8+ years of experience as a backend software engineer
  • Expert in TypeScript and JavaScript
  • Solid grasp of architectural concepts in large-scale distributed systems
  • Expertise in multiple storage systems (Relational Databases, Key-Value Stores, Cloud Buckets, etc.)
  • Strong experience in building enterprise-grade security features, including:
    • Role-based access control
    • API Key Management
    • Authentication and authorization (Auth0)
    • Single Sign-On (SSO) using identity providers
    • Audit trail
  • Extensive experience with public cloud platforms: 
    • Google Cloud Platform (GCP) (preferred)
    • Amazon Web Services (AWS)
    • Microsoft Azure
  • Working knowledge of orchestration systems, such as Kubernetes
  • Familiarity with DevOps technologies, including ArgoCD, CodeFresh, and DataDog

Nice to Have

  • Expertise in building streaming ETL pipelines
  • Proficiency in Kotlin and Python
  • Familiarity with ReactJS and front-end development techniques
  • Experience with asynchronous messaging systems (Kafka, Google Pub/Sub, AWS SQS, RabbitMQ)
  • An understanding of microservices architecture
  • Knowledge of Google Spanner and ElasticSearch

Engineering at Labelbox

We build a comprehensive platform and end-to-end tool suite for AI system development. We believe in providing the best user experience at scale with high quality. Our customers use our platform in production environments, daily, to build and deploy AI systems that have a real positive impact in the world. 

We believe in collaborative excellence and shared responsibility with decision making autonomy wherever possible. We strive for a great developer experience with continuous fine tuning. How we work is one of the cornerstones of engineering excellence at Labelbox.

We learn by pushing boundaries, engaging in open debate to come up with creative solutions, then committing to execution. We continuously explore and exploit new technologies, creating new and perfecting existing techniques and solutions. Making customers win is our North Star.

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Annual base salary range
$170,000$225,000 USD

Excel in a remote-friendly hybrid model.

We are dedicated to achieving excellence and recognize the importance of bringing our talented team together. While we continue to embrace remote work, we have transitioned to a hybrid model with a focus on nurturing collaboration and connection within our dedicated tech hubs in the San Francisco Bay Area, New York City Metro Area, and Wrocław, Poland. We encourage asynchronous communication, autonomy, and ownership of tasks, with the added convenience of hub-based gatherings.

Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.

Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

Labelbox
Labelbox
Artificial Intelligence Computer Vision Enterprise Software Machine Learning Software

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