Applied Research Engineer

HRB; San Francisco (CA); Vor Ort; USD 180.000 - 280.000; Vollzeit

Zusammenfassung

HRB is seeking an Applied Research Engineer to drive cutting-edge AI alignment and data-quality initiatives for frontier models. You will develop systems to collect and refine human-in-the-loop data, pushing the boundaries of RLHF and related techniques.

You will collaborate with researchers and engineers to translate novel insights into scalable tools and workflows, contributing to publication-ready research and practical AI solutions.

Qualifikationen

• Ph.D. or Master’s degree in CS/ML/AI or related field.
• 3+ years solving complex ML challenges.
• Experience designing data quality measurement and refinement systems.
• Understanding frontier AI models and human data strategies.
• Proficiency in Python and DL frameworks (PyTorch/JAX/TensorFlow).
• Track record of publishing in top AI/ML conferences.
• Ability to translate research findings into functional prototypes.

Aufgaben

• Develop and operationalize systems to create, analyze, and leverage high-quality human-in-the-loop data for frontier model developers.
• Design and implement methods to measure and improve human data quality for AI training.
• Create AI-assisted labeling tools to improve efficiency and accuracy of data labeling.
• Experiment with RLHF, DPO, and other alignment techniques in practical settings.
• Bridge research with product development by integrating breakthroughs into the company’s offerings.
• Publish and present research insights to the AI community and internal stakeholders.

Kenntnisse

Machine learning

Python

PyTorch

JAX

TensorFlow

Analytics

Communication

Ausbildung

Ph.D. or Master’s in CS/ML/AI

Tools

PyTorch

JAX

TensorFlow

Jobbeschreibung

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.

About Us

We're the only company offering three integrated solutions for frontier AI development:

• Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
• Frontier Data Labeling Service: Specialized data labeling through Aligner, leveraging subject matter experts for next-generation 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.
• Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.
• Clear Ownership: 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.

Role Overview

As an Applied Research Engineer, 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.

Your Impact

• 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.
• Improve the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training.
• 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.
• 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.
• Optimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness.
• Bridge research and real-world application by integrating breakthroughs into our product suite, making human-AI alignment techniques scalable and impactful for users.
• Drive industry innovation by engaging with customers and the broader AI community to understand evolving data needs and share best practices for training frontier models.
• Contribute to the AI research ecosystem by publishing in top-tier journals, presenting at leading conferences, and influencing the future of human-centric AI.
• Stay ahead of AI advancements by continuously exploring new frontiers in human-AI collaboration, human data quality, and AI alignment, keeping us at the cutting edge.
• Establish us as a thought leader in AI by creating technical documentation, blog posts, and educational content that shape the industry's approach to human-centric AI development.

What You Bring

• A strong foundation in AI and machine learning, backed by a Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related field.
• Proven experience (3+ years) in solving complex ML challenges and delivering impactful solutions that improve real-world AI applications.
• Expertise in designing and implementing data quality measurement and refinement systems that directly enhance model performance and reliability.
• A deep understanding of frontier AI models—such as large language models and multimodal models—and the human data strategies needed to optimize them.
• Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow to prototype and develop cutting-edge solutions.
• A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community.
• The ability to bridge research and application by interpreting new findings and rapidly translating them into functional prototypes.
• Strong analytical and problem-solving skills that enable you to tackle ambiguous AI challenges with structured, data-driven approaches.
• Exceptional communication and collaboration skills, allowing you to work effectively across multidisciplinary teams and with external stakeholders.