Applied Research Engineer
Applied Research Engineer
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Job Description
Position: Applied Research Engineer
Location - San Francisco CA - Hybrid
Job Type: Full Time
Job Description:
Role OverviewAs an Applied Research Engineer at Labelbox youll play a critical role in shaping the future of human-in-the-loop AI systems. Youll design and implement advanced methods to align human feedback with the training of cutting-edge AI models including techniques like Reinforcement Learning from Human Feedback (RLHF) Direct Preference Optimization (DPO) and other alignment strategies. Youll also develop innovative tools to measure and enhance the quality of human-generated data and build AI-assisted systems that streamline and improve the data labeling process.
Your work will directly influence the performance and reliability of frontier models by ensuring they reflect human preferences more accurately. By bridging research with real-world applications youll help bring scalable impactful alignment solutions into production for some of the worlds most advanced AI developers.
Your Impact- Drive advances in AI alignment developing state-of-the-art techniques like RLHF and new methods to ensure models align with human intent.
- Improve human-in-the-loop data quality by building robust systems for measurement feedback analysis and refinement.
- Create AI-assisted labeling tools using active learning adaptive sampling and automation to enhance speed and accuracy.
- Investigate the role of different feedback types-like preferences critiques and demonstrations-on model training and alignment.
- Develop algorithms to improve how AI systems learn from human input increasing adaptability and response quality.
- Integrate alignment innovations into the Labelbox product suite making human feedback workflows scalable for customers.
- Collaborate with customers and the AI research community to shape best practices for training large-scale models.
- Contribute to the field through publications conference presentations and open research.
- Stay ahead of the curve by exploring emerging trends in AI alignment data quality and human-AI collaboration.
- Help establish Labelbox as a thought leader in human-centric AI by producing high-quality technical and educational content.
- Advanced degree (Ph.D. or Masters) in Computer Science Machine Learning AI or a related field.
- 3 years of experience solving complex ML challenges and building production-ready AI systems.
- Proven track record in data quality systems with a strong understanding of how they affect model performance.
- Deep knowledge of frontier models including large language models and multimodal systems and how to optimize them using human feedback.
- Strong programming skills in Python with hands-on experience in PyTorch JAX or TensorFlow.
- Contributions to the research community through peer-reviewed publications in top AI/ML conferences (e.g. NeurIPS ICML ICLR ACL EMNLP NAACL).
- Ability to translate research into real-world solutions from prototype to scalable deployment.
- Strong analytical thinking and a structured approach to solving open-ended AI problems.
- Excellent collaboration and communication skills to work effectively across technical teams and with external stakeholders.
Employment Type
Full-time
