Labelbox · 19 hours ago
Full-Stack Engineer, AI Data Platform
San Francisco Bay Area
Full-time
Hybrid
Entry, Mid Level
$130K/yr - $200K/yr
2+ years expLabelbox is building critical infrastructure for AI models at leading research labs and enterprises. The Full-Stack Engineer will develop tools for AI systems, focusing on human-in-the-loop processes to generate high-quality training data for AI models.
AI InfrastructureArtificial Intelligence (AI)Computer VisionData Collection and LabelingEnterprise SoftwareMachine LearningSoftware
Responsibilities
Own End-to-End Product FeaturesDesign, build, and ship complete workflows spanning frontend UI, APIs, backend services, databases, and production infrastructure
Enable Human-in-the-Loop AI TrainingBuild systems that allow humans to efficiently create, review, and curate high-quality training and evaluation data used in AI model development
Support RLHF and Preference Data WorkflowsDesign and implement tooling that supports RLHF-style pipelines, including task generation, human review, scoring, aggregation, and dataset versioning
Leverage LLMs in the Review LoopBuild systems that use LLMs to assist human reviewers—such as automated checks, critiques, ranking suggestions, or quality signals—while maintaining human oversight
Advance AI EvaluationDesign and implement evaluation frameworks and interactive tools for LLMs and AI agents across multiple data modalities (text, images, audio, video)
Create Intuitive, Reviewer-Focused InterfacesBuild thoughtful, efficient user interfaces (e.g., in React) optimized for high-throughput human review, quality control, and operational workflows
Architect Scalable Data & Service LayersDesign APIs, backend services, and data schemas that support large-scale data creation, review, and iteration with strong guarantees around correctness and traceability
Solve Ambiguous, Real-World ProblemsTranslate loosely defined operational and research needs into practical, scalable, end-to-end systems
Ensure System ReliabilityParticipate in on-call rotations to monitor, troubleshoot, and resolve issues across the full stack
Elevate the TeamImprove engineering practices, development processes, and documentation. Share knowledge through technical writing and design discussions
Qualification
Required
Bachelor's degree in Computer Science, Data Engineering, or a related field
2+ years of experience in a software or machine learning engineering role
A proactive, product-focused mindset and a high degree of ownership, with a passion for building solutions that empower users
Experience using frontend frameworks like React/Redux and backend systems and technologies like Python, Java, GraphQL; familiarity with NodeJS and NestJS is a plus
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)
Familiarity with cloud infrastructure like GCP (GCS, PubSub) and containerization (Kubernetes) is a plus
Excellent communication and collaboration skills
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
A focus on writing clean, well-tested code and delivering your work on time
Preferred
Experience building tools for AI/ML applications, particularly for data annotation, monitoring, or agent evaluation
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)
Experience in optimizing databases for performance (e.g., schema design, indexing, query tuning) and integrating them with broader data workflows
Company
Labelbox
Labelbox is the leading data factory for AI teams.
51-200 employees
H1B Sponsorship
Labelbox has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (14)
2024 (6)
2023 (6)
2022 (7)
2021 (3)
2020 (3)
Funding
Current Stage
Late StageTotal Funding
$188.9MKey Investors
SoftBank Vision FundAndreessen HorowitzGradient
2022-01-06Series D· $110M
2021-02-11Series C· $40M
2020-02-04Series B· $25M
Leadership Team
Manu Sharma
CEO & Co-founder
Recent News
2025-11-02
2025-06-20
Company data provided by crunchbase