Senior Backend Engineer

San Francisco, CA, United States

Labelbox is the leading data-centric AI platform for building intelligent applications. Teams looking to capitalize on the latest advances in generative AI and LLMs use the Labelbox platform to inject these systems with the right degree of human supervision and automation. Whether they are building AI products by using LLMs that require human fine-tuning, or applying AI to reduce the time associated with manually-intensive tasks like data labeling or finding business insights, Labelbox enables teams to do so effectively and quickly.

Current Labelbox customers are transforming industries within insurance, retail, manufacturing/robotics, healthcare, and beyond. Our platform is used by Fortune 500 enterprises including Walmart, Procter & Gamble, Genentech, and Adobe, as well as hundreds of leading AI teams. We are backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures (Google's AI-focused fund), Databricks Ventures, Snowpoint Ventures and Kleiner Perkins.

About the Role

As a Senior Backend Software Engineer on Labelbox's Model Team, you'll architect solutions for a leading AI platform, focusing on a model-inferencing application to enhance labeling workflows. Your role is central to strengthening the scalability, robustness, and reliability of our backend, managing vast data streams and refining our ingestion pipeline. As we continue to grow, your expertise will be paramount in navigating the complexities and challenges of the ever-evolving AI domain. Join us in shaping efficient AI solutions for the future, and be part of a team that's redefining the AI landscape.

About You

8+ years of experience as either a full-stack or backend software engineer

Experience in a modern programming language (Typescript, Python, Java)

Expertise in multiple storage systems (Relational Databases, Document databases, etc.)

Experience in designing and developing in microservice-oriented architecture and distributed systems, with well defined APIs and scalable ecosystem

Familiarity with messaging frameworks such as pub/sub and RabbitMQ

Experience with Google Cloud Platform or AWS

Familiarity with DevOps technologies (ArgoCD, CodeFresh, Kubernetes, etc.)

Nice to Have

Experience in building ML workflows

Experience in designing highly scalable services and improving reliability through instrumentation of better logging, monitoring and testing

Your Day to Day

Design, build, deploy and maintain our complex backend systems for curating millions of unstructured data and ingesting vast data streams into a performant model-inferencing engine

Improve on our system architecture by setting a high quality bar with focus on highly scalable and robust services that meet enterprise-level requirements

Spread culture of applying solid engineering practices

Effectively communicate and collaborate with stakeholders on complex technical ideas

Uphold a high standard of code quality for both your own work and during code reviews

Identify, triage, and address in-production defects within established SLAs

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 $190,000 - $225,000. 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.

Excel in a Hub-centric Remote Model.

We’re committed to excellence and understand the importance of bringing our talented people together. While we continue to embrace remote work, we’ve transitioned to a Hub-Centric Remote Model with a focus on nurturing collaboration and connection within our dedicated hubs in the San Francisco Bay Area, New York City Metropolitan Area, Miami-Fort Lauderdale Area, and Warsaw, Poland. We encourage asynchronous communication, autonomy, and ownership of your 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. If you are uncertain about the legitimacy of any communication you have received, please do not hesitate to reach out to us at [email protected] for clarification and verification.

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