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Labelbox Jobs (NOW HIRING)

Labelbox

Applied Research Intern

San Francisco, CA ยท On-site

About Labelbox We're the only company offering three integrated solutions for frontier AI development: * Enterprise Platform & Tools : Advanced annotation tools, workflow automation, and quality ...

Labelbox

Applied Research Engineer

San Francisco, CA ยท On-site

$250K - $300K/yr

About Labelbox We're the only company offering three integrated solutions for frontier AI development: * Enterprise Platform & Tools : Advanced annotation tools, workflow automation, and quality ...

Labelbox

Applied Research Intern

San Francisco, CA

Role Overview As an Applied Research intern at Labelbox, you will design, build, and productionize evaluation and posttraining systems for frontier LLMs and multimodal models. You'll own continuous ...

Labelbox

Forward Deployed Engineer

San Francisco, CA ยท On-site

$140K - $200K/yr

About Labelbox We're the only company offering three integrated solutions for frontier AI development: * Enterprise Platform & Tools : Advanced annotation tools, workflow automation, and quality ...

Labelbox

Applied Research Engineer

San Francisco, CA

Role Overview Applied Research at Labelbox builds the benchmarks and data that drive the next generation of foundational agentic capabilities. We are looking for exceptional researchers and research ...

Labelbox

Managing Partner, Frontier AI

San Francisco, CA

$137K/yr

Expand wallet share by uncovering new project streams, embedding Labelbox as a strategic partner across evaluation, red teaming, SFT, RLHF, and benchmark initiatives. * Elevate Go-to-Market Strategy

Labelbox

Forward Deployed Engineer

San Francisco, CA

Alignerr Services at Labelbox As part of the Alignerr Services team, you'll lead implementation of customer projects and manage our elite network of AI experts who deliver high-quality human feedback ...

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How much do labelbox jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for labelbox in the United States is $26.34, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $30.77 per hour, depending on experience, location, and employer.

What are some common challenges faced when working in a data labeling role using Labelbox?

One of the main challenges in a data labeling role using Labelbox is maintaining consistency and accuracy across large datasets, especially when dealing with complex or ambiguous data. Adhering to specific labeling guidelines and quality standards can require ongoing focus and attention to detail, and occasionally you may need to collaborate with data scientists or machine learning engineers to clarify requirements. Staying organized while meeting tight project deadlines is also common, particularly when supporting fast-paced AI development cycles. However, these challenges present valuable opportunities to build technical expertise, contribute significantly to impactful AI projects, and advance your career in the rapidly growing field of machine learning operations.

Is Labelbox a good company to work for?

Labelbox is a technology company specializing in data labeling and management tools, often hiring for roles related to software engineering, data annotation, and product development. Employee reviews indicate a collaborative environment with opportunities for growth, though experiences can vary based on role and location.

What is a Labelbox job?

A Labelbox job is a task or project within the Labelbox platform that involves annotating, labeling, or reviewing data for machine learning models. Companies use Labelbox to manage large-scale data labeling efforts for images, videos, text, and more. Jobs can be assigned to annotators who apply labels according to predefined guidelines. These labels help train AI models by providing high-quality training data.

What are the key skills and qualifications needed to thrive in the Labelbox position, and why are they important?

To thrive in a Labelbox role, such as a Data Annotation Specialist or Machine Learning Data Operations, you need a keen attention to detail, basic data management skills, and a foundational understanding of labeling processes for AI datasets. Familiarity with cloud-based annotation platforms like Labelbox, as well as experience with tools such as Excel or basic image and text editing software, is highly valuable. Strong communication, adaptability, and time management skills are important for effectively handling labeling tasks within cross-functional teams. These capabilities are essential for ensuring high-quality, accurate data labeling that supports effective machine learning model development.

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Labelbox jobs near you
Infographic showing various Labelbox job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 9% Part Time, and 6% Contract. Highlights an 52% Physical, and 48% Remote job distribution, with an average salary of $54,791 per year, or $26.3 per hour.
Applied Research Intern

Applied Research Intern

Labelbox

San Francisco, CA โ€ข On-site

Full-time, Internship

Posted yesterday

Job description

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 AI development:
  1. Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
  2. Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models
  3. Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling
Why Join Us
  • High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.
  • Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.
  • Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.
  • Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.
  • Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.

Role Overview
As an Applied Research intern at Labelbox, you will design, build, and productionize evaluation and post-training systems for frontier LLMs and multimodal models. You'll own continuous, high-quality evals and benchmarks (reasoning, code, agent/tool-use, long-context, vision-language, et al.), create and curate post-training datasets (human + synthetic), and prototype RLHF/RLAIF/RLVR/RM/DPO-style training loops to measure and improve real-world task and agent performance.
Your Impact
  • Build and own evaluation and benchmark suites for reasoning, code, agents, long-context, and V/LLMs.
  • Create post-training datasets at scale: design preference/critique pipelines (human + synthetic), and target hard failures surfaced by evals.
  • Experiment and prototype RLHF/RLAIF/RLVR/RM/DPO-style training loops to improve real-world task and agent performance.
  • Land research in product: ship improvements into Labelbox workflows, services, and customer-facing evaluation/quality features; quantify impact with customer and internal metrics.
  • Engage with customer research teams: run pilots, co-design benchmarks, and share practical findings through internal research reports, blog posts, talks, and published papers.
What You Bring
  • A strong foundation in AI and machine learning, backed by a Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field (in progress degrees are acceptable for intern positions).
  • A deep understanding of frontier autoregressive and diffusion multimodal models, along with the human and synthetic data strategies needed to optimize them.
  • Passion and experience for LLM evaluation and benchmarking.
  • Expertise in training data quality construction, measurement and refinement.
  • The ability to bridge research and application by interpreting new findings and translating them into functional prototypes.
  • A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community.
  • Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow.
  • Exceptional communication and collaboration skills.
Applied Research at Labelbox
At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advancing human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios.
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
$35-$45 USD
Life at Labelbox
  • Location: Join our dedicated tech hubs in San Francisco or Wrocล‚aw, Poland
  • Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility
  • Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making
  • Growth: Career advancement opportunities directly tied to your impact
  • Vision: Be part of building the foundation for humanity's most transformative technology
Our Vision
We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs.
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.
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.

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