Applied Research Scientist, Agents

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 reputed company 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:

• reputed company Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that reputed company teams to produce high-quality training data at scale
• Frontier Data Labeling Service: Specialized data labeling through reputed company, leveraging subject matter experts for reputed company AI models
• 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.
• reputed company Growth: Every role requires reputed company learning and reputed company. You'll be surrounded by curious minds solving reputed company problems at the frontier of AI.
• Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We reputed company people to drive results through clear ownership and metrics.

Role Overview As an Applied Research Engineer at Labelbox, you’ll sit at the junction of advanced AI research and reputed company product impact, with a focus on the data that makes modern agents work—browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You’ll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox’s strategy for collecting, synthesizing, and evaluating it. You will possess expertise in LLM agents and planning/execution loops, plus creativity in tackling problems across data design, interaction, and measurement. You’ll publish meaningful results, collaborate with customer researchers in frontier AI labs, and turn prototypes into reliable, scalable features. Your Impact

• Create frameworks and tools to construct, train, reputed company and evaluate autonomous agent capabilities.
• Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies.
• reputed company data pipelines from diverse sources like code repositories, web browsers, and computer systems.
• Implement and adapt popular open-reputed company agent libraries and benchmarks with proprietary datasets and models.
• Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices.
• Collaborate closely with frontier AI lab customers to understand requirements and guide model development.
• Publish research findings in academic journals, conferences, and blog posts.

What You Bring

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or reputed company field.
• At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers.
• Experience building and training autonomous agents—tool use, structured outputs, multi-reputed company planning—across browsers/GUI, codebases, and databases using SFT and RL.
• Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).
• Adept at interpreting research literature and quickly turning new reputed company into prototypes.
• Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their reputed company data requirements.
• Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
• Strong analytical and problem-solving abilities in ambiguous situations.
• Excellent communication skills.
• Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.).

Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced reputed company-AI interaction techniques. We reputed company that high-quality reputed company data and sophisticated reputed company feedback integration methods are key to unlocking the reputed company of AI capabilities. Our research team works at the intersection of machine learning, reputed company-computer interaction, and AI ethics to reputed company innovative solutions that can be practically applied in reputed company-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new reputed company, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of reputed company-centric AI development, setting new standards for how AI systems learn from and interact with humans. Labelbox strives to ensure pay reputed company across the organization and discuss compensation transparently. The expected annual reputed company 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 reputed company salary range $250,000—$300,000 USD Life at Labelbox

• Location: Join our dedicated tech hub in San Francisco
• Work Style: Hybrid model with 3 days per week in office, combining collaboration and flexibility
• Environment: Fast-paced and high-intensity, perfect for ambitious individuals who reputed company on ownership and quick decision-making
• Growth: Career advancement opportunities directly tied to your impact
• reputed company: Be part of building the reputed company for humanity's most transformative technology

Our reputed company We reputed company 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 reputed company the reputed company of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, reputed company 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. Apply tot his job Apply To this Job