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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.
We're the only company offering three integrated solutions for frontier AI development:
As a Forward Deployed Engineer Intern, you will work alongside a senior FDE on real client engagements with leading AI labs. You will own concrete pieces of those engagements - writing scripts to process and analyze data, building automated quality checks, and helping validate that the data we deliver is good enough to ship. The work is hands-on, fast-paced, and rarely arrives with a complete spec.
This is not a shadowing internship. You will be expected to take ownership of your projects, work through ambiguity with your manager, and ship work that real clients depend on. If you do well, you will see your work translate directly into how frontier AI models are trained and evaluated.
Labelbox builds the data infrastructure behind frontier AI development. We work with leading research labs and enterprises to produce the high-quality datasets used for evaluation, supervised fine-tuning, and reinforcement learning. The Frontier AI team you will be joining sits at the intersection of engineering and applied research, working directly with AI lab partners on some of the most demanding data problems in the industry.
We care more about how you think than about a specific list of credentials. The things below are what tend to make interns successful in this role:
FDE work at Labelbox is a spot where it spans engineering, research, and direct client work. As an intern, you will get exposure to all three - and to the kinds of problems that most engineering internships do not touch. You will work with people who care about getting the technical details right and who will give you the room to do the same.
This is a paid internship with an hourly rate of $50-$70 per hour.
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.
Ready to apply?
Apply to Labelbox
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.
We're the only company offering three integrated solutions for frontier AI development:
We’re hiring a Forward Deployed Engineering Manager to lead the design, development, and delivery of reinforcement learning environments for agentic AI systems.
You’ll manage a team responsible for building sandboxed, reproducible environments—terminal-based workflows, browser automation, and computer-use simulations—that power both model training and human-in-the-loop evaluation. This is a hands-on leadership role where you’ll set technical direction, guide execution, and stay close to architecture and critical systems.
Required
Preferred
RL environment quality is a critical bottleneck in advancing agentic AI. Poorly designed or unreliable environments introduce noise into training loops and directly impact model performance.
In this role, you’ll lead the team building the environments that define how models learn—working across a range of cutting-edge projects with leading AI labs. Alignerr offers the speed and ownership of a startup with the scale and resources of Labelbox, giving you the opportunity to have outsized impact on the future of AI.
Alignerr is Labelbox’s human data organization, powering next-generation AI through high-quality training data, reinforcement learning environments, and evaluation systems. We partner directly with leading AI labs to build the data and infrastructure that push model capabilities forward.
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.
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.
Ready to apply?
Apply to Labelbox
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.
We're the only company offering three integrated solutions for frontier AI development:
Alignerr is Labelbox's human data organization — we produce the training data that frontier AI labs use to build their most capable models. Our Forward Deployed Research Team sits at the intersection of research science and client delivery, embedding research capability directly into the engagements that drive our business.
This is not a traditional research scientist role. You will not spend months pursuing a single research question. You will work on multiple client engagements simultaneously, operating on timescales of days to weeks. You will sit in scoping meetings with research teams at major AI labs, reason scientifically about data strategy in real time, fine-tune open-weight models to validate our data methodology, and collaborate with our Applied Research team to turn client-grounded findings into published work. The pace is fast, the problems are applied, and the feedback loops are short.
We are looking for someone who finds that energizing, not compromising.
Engage directly with frontier lab research teams. You will be in the room during client scoping meetings — not as support staff, but as a technical peer. You'll engage on methodology, challenge assumptions about data requirements, and shape project specifications based on a scientific understanding of how data composition affects model outcomes.
Develop deep scientific understanding of client engagements. For each project, you will build a working model of the client's architecture, training methodology, and target capabilities. You'll use this understanding to reason about why a particular data strategy will or won't work, identify risks early, and iterate with empirical grounding — not intuition.
Run ablation studies and fine-tune open-weight models. You will fine-tune models on client data (and proxy data) to empirically measure the impact of our data on model performance. This is how we validate that what we deliver actually improves our customers' models — and how we catch problems before the client does.
Consult on workflow and quality systems. You will partner with our Human Data Operations team to review annotation schemas, task designs, and quality rubrics before projects go into execution. Your job is to ensure the spec is technically sound — that the data we produce will actually serve the client's training objectives.
Collaborate with Applied Research on publications and benchmarks. Our Applied Research team owns the long-horizon research agenda. Your role is to feed them signal from the field — generalizable findings, reusable methodologies, empirical results — and help drive joint projects to completion. You will contribute to benchmarks, white papers, and conference submissions that establish Labelbox's research credibility.
Required
Strongly Preferred
What Matters More Than Credentials
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.
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.
Ready to apply?
Apply to Labelbox
Share this job
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.
We're the only company offering three integrated solutions for frontier AI development:
The Role
We’re hiring a Forward Deployed Engineer to own the design, development, and operationalization of reinforcement learning environments. You’ll build the sandboxed, reproducible execution environments that AI agents interact with during training and evaluation—things like terminal-based task benchmarks, browser and computer-use environments, and tool-augmented agentic workspaces.
This is a hands-on engineering role. You’ll write production-quality infrastructure code, integrate with open-source RL tooling, and work closely with our data operations team to ensure environments are robust, observable, and ready for human annotators and model agents alike. You won’t be doing ML research, but you’ll need to deeply understand how RL training loops consume environments and where the bottlenecks live.
What You’ll Do
What We’re Looking For
Required
Preferred
Candidate Archetype
The ideal candidate is a strong software engineer first, with genuine curiosity and working knowledge of reinforcement learning. You’ve probably built infrastructure or developer tooling at a startup or mid-stage company, and you’ve been pulled toward the ML/AI space—maybe through side projects, open-source contributions, or a prior role adjacent to an ML team. You’re the kind of engineer who reads an RL benchmark paper and immediately thinks about how to make the environment more robust, not how to improve the policy gradient.
You thrive in ambiguity. You can take a loosely defined project requirement—“build an environment that tests an agent’s ability to navigate a file system and execute multi-step bash workflows”—and deliver a working, tested, documented system without needing a detailed spec. You move fast, but you care about reliability because you know environments that break silently poison training data.
Why This Role Matters
Alignerr is Labelbox’s human data organization, purpose-built to generate the high-quality training data that powers the next generation of AI models. We partner directly with leading AI labs to produce reinforcement learning environments, evaluation benchmarks, and expert-annotated datasets that push model capabilities forward. Our team sits at the intersection of software engineering, ML infrastructure, and human-in-the-loop data production.
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.
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.
Ready to apply?
Apply to Labelbox
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.
We're the only company offering three integrated solutions for frontier AI development:
Get an inside look and hear directly from our current Forward Deployed Engineers here!
This role requires an entrepreneurial mindset. You will operate like a technical cofounder: with high agency, deep technical engagement, and a bias for action.
You will use a unique mix of engineering, product, and sales to deliver data on high stakes projects for leading frontier AI labs. You will work with human data teams or AI researchers in customer organizations to produce the best datasets for model evals, supervised finetuning, or ground truth data for advanced and emerging reinforcement learning techniques.
Understand the Data Needs of AI Leaders: Work directly with the most advanced AI labs to define and refine data strategies.
Design and Operate Human Data Pipelines: Build scalable, high-quality data pipelines to power next-gen AI.
Develop and Optimize Code: Write Python scripts for data processing and quality analysis.
Shape the Future of AI Infrastructure: Define engineering requirements to improve human data tools and workflows.
Master’s degree or higher in Computer Science, Engineering, Mathematics, or AI-related fields.
Proficiency in Python and data analysis.
Exceptional communication skills: ability to convey complex technical concepts clearly.
Strong project management and organizational skills.
Passion for AI and the intersection of technology, product, and customer needs.
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 crucial for AI advancement. Your team will oversee 250,000+ monthly hours of specialized work across RLHF, complex reasoning, and multimodal AI projects, resulting in quality improvements for Frontier AI Labs. You'll leverage our AI-powered talent acquisition system and exclusive access to 16M+ specialized professionals to rapidly build and deploy expert teams that help customers, which include the majority of leading AI labs and AI disruptors, achieve breakthrough AI capabilities through precisely aligned human data—directly contributing to the critical human element in advancing artificial intelligence.
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.
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.
Ready to apply?
Apply to Labelbox
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