Job Details

Applied Research Intern

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:

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

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.

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.

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.

Annual base salary range $35 - $45 USD

Join our dedicated tech hubs in San Francisco or Wroc?aw, Poland

Hybrid model with 2 days per week in office, combining collaboration and flexibility

Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making

Career advancement opportunities directly tied to your impact

Be part of building the foundation for humanity's most transformative technology