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Clariti's CivCheck platform aims to transform how cities manage plan review and building code compliance by streamlining and modernizing the permitting process using AI. The AI Researcher will help translate machine learning research into practical, domain-specific proofs of concept to enhance this platform.

Requirements

• Demonstrated experience training and fine-tuning models from scratch using modern frameworks — including defining layer-level architectures, curating & cleaning datasets, tuning training parameters, and monitoring training/validation set performance
• Proficiency in Python and C/C++
• Proficiency with PyTorch, TensorFlow, JAX, or similar deep learning frameworks
• Strong software engineering skills with familiarity with best practices in version control (Git), testing, and modular design
• Experience implementing core computer vision and image processing algorithms, including feature extraction, object detection, segmentation, and geometric transformations
• Strong experimental and statistical intuition; comfortable interpreting complex results
• Familiarity with LLMs, diffusion models, model distillation, or multimodal architectures

Responsibilities

• Read, interpret, and implement recent ML research papers into functioning prototypes
• Design and Conduct experiments to validate research ideas, define test metrics/ hypotheses, and evaluate model performance
• Apply research to specific computer vision problem domains, tailoring architectures and training strategies for best results on complex unstructured data
• Tailor and apply foundational ML techniques to real-world datasets and use cases
• Collaborate with engineering teams on model deployment, monitoring and enhancement
• Contribute to internal research documentation and share findings with the broader AI team
• Identify and prototype potential improvements to our AI systems based on current literature

Other

• Bachelor's degree or Master’s degree in Computer Science, Mathematics, or a related analytical STEM field with specialization in machine learning
• 1–3 years of hands-on experience in applied ML or research (flexible for strong academic backgrounds)
• Excellent communication skills, you can explain research clearly to both technical and non-technical audience
• Experience teaching or mentoring machine learning coursework or project-based work
• Interest in the ethical implications of AI technology and responsible AI development and design