AI / Machine Learning Researcher
We are searching for an AI / Machine Learning Researcher to join our AI team and focus on applied research for real-world product challenges. You will work with raw data, explore new approaches, formulate and test hypotheses, and build prototypes and MVP solutions that can later become production features within the Planner 5D platform.
Conduct applied research in AI/ML to solve real-world problems related to home design, 2D/3D data, and visual understanding.
Work with raw and unstructured data (images, 3D point clouds, text, video) to identify useful signals and formulate research directions.
Generate and test hypotheses through experiments, modeling, and data analysis.
Design and implement prototypes and MVP solutions, validating ideas before production implementation.
Train, evaluate, and iterate on machine learning and deep learning models.
Contribute to the development of AI-driven features, including computer vision systems and AI agents.
Collaborate with engineers to translate research prototypes into production-ready solutions.
Provide algorithm-level support for deployed models, improving and adapting them as new data or requirements emerge.
4+ years of experience in AI/ML research or applied machine learning.
Strong background in mathematics and computer science, including statistics, optimization, linear algebra, and algorithms.
Solid understanding of machine learning and deep learning methods.
Experience working with real-world datasets, including data exploration, cleaning, feature extraction, and experimental validation.
Proficiency in Python and common scientific/ML libraries (NumPy, SciPy, Pandas, etc.).
Experience with deep learning frameworks such as TensorFlow or PyTorch.
Familiarity with computer vision or multimodal AI (images, video, 3D data such as point clouds and meshes).
Ability to independently formulate research hypotheses, design experiments, and evaluate results.
Strong analytical thinking and ability to solve complex problems with limited prior solutions.
Experience with 3D data processing (point clouds, meshes, spatial data).
Experience building or experimenting with AI agents or LLM-based systems.
Experience training and fine-tuning neural networks.
Interest in geometry, graph theory, or computational geometry.
