Applied Research Engineer

Join the Future of Human-Centered AI Were on a mission to build the critical infrastructure powering the next generation of AI. Since 2018, weve led the charge in data-centric AI developmentcombining top-tier tools, expert data labeling, and scalable human feedback systems to shape frontier models. Our three integrated solutions fuel AI innovation: - Enterprise Platform & Tools: Advanced annotation tools and workflow automation for high-quality training data at scale. - Frontier Data Labeling Services: Expert-driven labeling for next-gen AI systems. - Expert Marketplace: A flexible, on-demand network of specialized annotators and domain experts. Why Join Us - High Impact: Work at a fast-paced, mission-driven company where your contributions matter. - Cutting-Edge Innovation: Tackle real challenges in AI alignment and human feedback systems. - Collaborative Excellence: Join a team of top researchers and engineers passionate about ethical AI. - Growth & Learning: Continuously learn, experiment, and grow your career in a high-caliber environment. - Clear Ownership: Take initiative, lead with autonomy, and see your work in production. What Youll Do - Develop novel methods to align AI systems with human intent using RLHF, DPO, and related approaches. - Design and build tools for collecting, evaluating, and optimizing human feedback in AI training. - Enhance data labeling pipelines through active learning, adaptive sampling, and AI-assisted workflows. - Analyze feedback types (demonstrations, comparisons, critiques) to improve model performance and safety. - Translate research into scalable, production-ready systems and contribute to platform innovation. - Publish at top ML/AI conferences and help shape industry best practices in alignment research. What You Bring - Masters or Ph.D. in Computer Science, Machine Learning, or related field. - 3+ years of experience applying ML to real-world problems, preferably in alignment or human-in-the-loop systems. - Deep understanding of data-centric AI, frontier model training, and feedback optimization. - Proficiency in Python and ML frameworks (e.g., PyTorch, JAX, TensorFlow). - A track record of research publications (NeurIPS, ICML, ICLR, ACL, etc.) is a strong plus. - Strong prototyping, problem-solving, and analytical thinking skills. - Excellent communication and a collaborative mindset. Our Mission Were redefining how AI learns from humans. By combining machine learning, human-computer interaction, and ethical AI research, we ensure every system we build is responsible, effective, and aligned with real-world human values. Originally posted on Himalayas