Applied Research Engineer

<div class="content-intro"><h2><strong>Shape the Future of AI</strong></h2> <p>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.</p> <h2><strong>About Labelbox</strong></h2> <p>We're the only company offering three integrated solutions for frontier AI development:</p> <ol> <li><strong>Enterprise Platform Tools</strong>: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale</li> <li><strong>Frontier Data Labeling Service</strong>: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models</li> <li><strong>Expert Marketplace</strong>: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling</li> </ol> <h2><strong>Why Join Us</strong></h2> <ul> <li><strong>High-Impact Environment</strong>: 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.</li> <li><strong>Technical Excellence</strong>: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.</li> <li><strong>Innovation at Speed</strong>: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.</li> <li><strong>Continuous Growth</strong>: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.</li> <li><strong>Clear Ownership</strong>: 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.</li> </ul></div><h2><strong>Role Overview</strong></h2> <p>As an Applied Research Engineer at Labelbox, you will be at the forefront of developing cutting-edge systems and methods to create, analyze, and leverage high-quality human-in-the-loop data for frontier model developers. Your role will involve designing and implementing advanced systems that align human feedback into AI training processes, such as Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), etc. You will also work on innovative techniques to measure and improve human data quality, and develop AI-assisted tools to enhance the data labeling process. Your expertise in machine learning, frontier model training, and advanced human data alignment techniques will be crucial in pushing the boundaries of AI capabilities and delivering state-of-the-art solutions to meet the evolving needs of our customers.</p> <h2><strong>Your Impact</strong></h2> <ul> <li>Advance the field of AI alignment by developing cutting-edge methods, such as RLHF and novel approaches, that ensure AI systems reflect human preferences more accurately.</li> <li>Improve the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training.</li> <li>Increase efficiency and effectiveness in AI-assisted data labeling by creating tools that leverage active learning and adaptive sampling, reducing manual effort while improving accuracy.</li> <li>Shape the next generation of AI models by investigating how different types of human feedback (e.g., demonstrations, preferences, critiques) impact model performance and alignment.</li> <li>Optimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness.</li> <li>Bridge research and real-world application by integrating breakthroughs into Labelbox’s prod ... (truncated, view full listing at source)