# Full-Stack Engineer, AI Data Platform

**Company:** [Labelbox](https://hotfix.jobs/companies/labelbox)
**Location:** San Francisco, CA
**Role:** Fullstack Engineering
**Salary:** $180k – $260k/yr
**Experience:** 5+ years
**Skills:** React, Redux, TypeScript, Python, Java, GraphQL, Node.js, Postgres, MySQL, Google Spanner, GCP, Kubernetes, Kafka, LLMs
**Posted:** 2026-07-07

> Build end-to-end human-in-the-loop AI data platform features for RLHF, evaluation, and LLM-assisted review workflows. Requires 3+ years software/ML engineering experience with React, Python, GraphQL, databases, and GCP/Kubernetes.

## Job Description

## Your Impact
- 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.
- Solve Ambiguous, Real-World Problems: Translate loosely defined operational and research needs into practical, scalable, end-to-end systems.
- Ensure System Reliability: Participate in on-call rotations to monitor, troubleshoot, and resolve issues across the stack.
- Elevate the Team: Re-imagine engineering practices, development processes, and documentation. Share knowledge through technical writing and design discussions.

## What You Bring
- Bachelor’s degree in Computer Science, Data Engineering, or a related field.
- 3+ 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).
- Working knowledge of cloud infrastructure like GCP (GCS, PubSub) and containerization (Kubernetes).
- 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.

## Bonus Points
- 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.

## Our Technology Stack
- Frontend: React.js with Redux, TypeScript
- Backend: Node.js, TypeScript, Python, some Java & Kotlin
- APIs: GraphQL
- Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes
- Databases: MySQL, Spanner, PostgreSQL
- Queueing / Streaming: Kafka, PubSub

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**Apply:** https://hotfix.jobs/jobs/371a52cb-fef7-4f1f-98a5-99e17b9a33d4
**Canonical:** https://hotfix.jobs/jobs/371a52cb-fef7-4f1f-98a5-99e17b9a33d4