Machine Learning Engineer
Dream Technologies
Machine Learning Engineer
Dream Technologies
Automates building design and engineering
We are looking for a Generative AI engineer to work on the full lifecycle of novel spatial generative AI model development, defining the correct frame of an inference problem, structuring image-based training data into usable formats, training and testing models, deploying performant systems into our production architecture stack.
Upcoming Challenges
Generate high quality renovation and home design layouts using state-of-the-art generative models.
Build a model that adapts to user feedback and suggests home design tailored to user preferences.
Define required datasets and work with labeling agencies to generate high quality data.
Deploy models to production environments and iterate with real users on real-world problems.
What we Require
MS in Computer Science with a focus or specialty in Machine Learning
2+ Years of experience training and deploying real-world AI . Deep understanding of model architectures, training pipelines, and evaluation methodologies.
Creativity and technical depth to explore, evaluate, and iterate on different machine learning approaches
Scrappiness and speed in getting models built and tested under real-world constraints.
Strong background in algorithms, data structures, and mathematics, with the ability to design performant solutions to spatial and generative problems.
Proficiency in Python, with a strong preference for experience using NumPy and PyTorch.
Automates building design and engineering
Dream Technologies builds built-world models to automate design and engineering in the architecture, engineering and construction (AEC) industry. Its models simulate real-world building behavior and use that insight to drive automated design decisions and engineering workflows, helping teams move from concept to constructible plans more quickly. The product works by leveraging specialized, domain-focused models that integrate with AEC processes to generate and optimize designs and engineering tasks. Dream differentiates itself through deep domain expertise from its founders, who have experience at Palantir, and a strong seed-stage backing from notable investors, signaling a focus on applying advanced analytics and decision-making to AEC workflows. Its goal is to reduce time, cost, and rework in building projects by delivering automated, data-driven design and engineering outcomes.
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