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
As a Senior Backend Engineer on the Platform engineering team, you’ll lead the development of key aspects of our core services, including data I/O, streaming and storage capabilities. In this role, you will drive the evolution of our data infrastructure , focusing on large-scale high-throughput import and export, enabling Labelbox customers to seamlessly stream data from Labelbox to their platform, supporting the development of next generation AI models.
Your Day to Day
- Design, Develop, Deploy: Lead the design, development, and deployment of critical backend systems for large-scale distributed data infrastructure, including high-throughput exports.
- Scalability & Performance: Architect highly scalable, secure, and performant systems to handle billions of records at blazing speeds.
- Customer Collaboration: Work directly with customers to understand their needs, troubleshoot issues, and continuously improve the platform based on their feedback.
- Project Leadership: Drive initiatives from concept to execution, collaborating across teams and acting as a project owner.
- Strategic Planning: Work closely with stakeholders to define the Platform team’s roadmap and work closely with senior leadership to shape the company’s future.
- Innovation in AI: Contribute to building new capabilities for an AI platform used by leading AI labs to develop powerful multi-modal large language models (LLMs).
About You
- 5-8+ years of experience as a backend software engineer
- Expertise in a modern programming language (Python, Java, Kotlin, or TypeScript)
- Proficient in multiple storage systems (Relational Databases, Key-Value Stores, Cloud Buckets, etc.)
- Strong understanding of architectural concepts for large-scale distributed systems
- Expertise in building streaming ETL pipelines
- Experience with asynchronous messaging systems (Kafka, Google Pub/Sub, AWS SQS, RabbitMQ)
- Extensive experience with one or more public cloud platforms:
- Google Cloud Platform (GCP) (preferred)
- Amazon Web Services (AWS)
- Microsoft Azure
Nice to Have
- Familiarity with ReactJS and front-end development techniques
- An understanding of microservices architecture
- Knowledge of Google Spanner and ElasticSearch
- Working knowledge of orchestration systems (e.g., Kubernetes)
- Familiarity with DevOps tools, such as ArgoCD, CodeFresh, and DataDog
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.
Top Skills
What We Do
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. Customers include Fortune 500 enterprises and leading AI labs, and Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins.
Why Work With Us
Labelboxers are driven to master their craft and build the best products for AI, which is quickly becoming one of the most significant technologies of our time. Join us in supporting our customers as they create AI breakthroughs.
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