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