Labelbox

Labelbox

Sr. Full-Stack Engineer, AI Data Platform

San Francisco Bay Area · Senior

Sponsorship not specified$180k-$260kDetected 15 days ago
TypeScriptPythonJavaKotlinReactReduxNode.jsBackend DevelopmentFull-Stack DevelopmentGitNoSQLPostgreSQLMySQLMongoDBElasticsearchCassandraDynamoDBAWSGCPCloud PlatformsKubernetesGraphQLKafkaMachine Learning

About the role

  • from user-facing experiences and APIs to backend services, data models, and infrastructure.
  • You'll be at the heart of our applied AI efforts, with a particular focus on human-in-the-loop systems used to generate high-quality training data for Large Language Models (LLMs) and AI agents.

Responsibilities

  • Own Large Surface: Design, build, and ship workflows spanning frontend UI, APIs, backend services, databases, and production infrastructure across a variety of features.
  • Enable Human-in-the-Loop AI Training: Build systems that allow humans to efficiently create, review, and curate high-quality AI training and evaluation data sets.
  • Support RLHF and Preference Data Workflows: Design and implement tooling that supports RLHF-style pipelines, including task generation, human review, scoring, aggregation, and dataset versioning.
  • Leverage LLMs in the Review Loop: Build systems that use LLMs to assist human reviewers, such as automated checks, critiques, ranking suggestions, or quality signals.
  • Advance AI Evaluation: Design and implement evaluation frameworks and interactive tools for LLMs and AI agents across multiple data modalities (text, images, audio, video).
  • Create Intuitive, Reviewer-Focused Interfaces: Build thoughtful, efficient user interfaces optimized for high-throughput human review, quality control, and operational workflows.
  • Architect Scalable Data & Service Layers: Design APIs, backend services, and data schemas that support large-scale data creation, review, and iteration with strong guarantees around correctness and traceability.
  • Elevate the Team: Re-imagine engineering practices, development processes, and documentation. Share knowledge through technical writing and design discussions.
  • We celebrate those who take ownership, move fast, and deliver impact.
  • Build systems that allow humans to efficiently create, review, and curate high-quality AI training and evaluation data sets.

Requirements

  • Bachelor's degree in Computer Science, Data Engineering, or a related field.
  • A proactive, product-focused mindset and a high degree of ownership, with a passion for building solutions that empower users.
  • Working knowledge of cloud infrastructure like GCP (GCS, PubSub) and containerization (Kubernetes).
  • High proficiency in leveraging AI tools for daily development (e.g., Cursor, GitHub Copilot).
  • Comfort and enthusiasm for working in a fast-paced, agile environment where rapid problem-solving is key.
  • Familiarity with data infrastructure components such as data pipelines, streaming systems, and storage architectures (e.g., Cloud Buckets, Key-Value Stores).
  • Previous experience with search engines (e.g., ElasticSearch).
  • Our team combines deep technical expertise with a passion for innovation, working at the intersection of AI infrastructure, data systems, and user experience.
  • 3+ years of experience in a software or machine learning engineering role.
  • Knowledge of designing and managing scalable database systems, including relational databases (e.g., PostgreSQL, MySQL), NoSQL stores (e.g., MongoDB, Cassandra), and cloud-native solutions (e.g., Google Spanner, AWS DynamoDB).
  • Excellent communication and collaboration skills.
  • A focus on writing clean, well-tested code and delivering your work on time.
  • Bonus Points
  • Experience building tools for AI/ML applications, particularly for data annotation, monitoring, or agent evaluation.

Nice to have

  • Experience using frontend frameworks like React/Redux and backend systems and technologies like Python, Java, GraphQL
  • familiarity with NodeJS and NestJS is a plus.

Skills

  • Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
  • Google Cloud Platform (GCP), Kubernetes
  • MySQL, Spanner, PostgreSQL

Compensation

  • The expected annual base salary range for United States-based candidates is below.
  • Annual base salary range
  • $180,000 - $260,000 USD

Benefits

  • Continuous Growth: Every role requires continuous learning and evolution.
  • This range is not inclusive of any potential equity packages or additional benefits.

Company info

  • Shape the Future of AI
  • At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises.
  • Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.
  • About Labelbox
  • We're the only company offering three integrated solutions for frontier
  • Experience using frontend frameworks like React/Redux and backend systems and technologies like Python, Java, GraphQL; familiarity with NodeJS and NestJS is a plus.
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This listing is sourced directly from Labelbox's careers page and normalized into a canonical job model.