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Dream Technologies

Automates building design and engineering

Machine Learning Engineer - Generative AI

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • A Master of Science degree in Computer Science with a focus or specialty in Machine Learning is required.
  • At least 2 years of experience training and deploying real-world artificial intelligence systems is required.
  • Deep understanding of model architectures, training pipelines, and evaluation methodologies is required.
  • Ability to explore, evaluate, and iterate on different machine learning approaches is required.
  • Ability to build and test models under real-world constraints is required.
  • Strong background in algorithms, data structures, and mathematics is required.
  • Ability to design performant solutions to spatial and generative problems is required.
  • Proficiency in Python is required.

Responsibilities

  • Develop novel spatial generative artificial intelligence models across the full lifecycle, including defining inference problems, structuring image-based training data, training and testing models, and deploying performant systems into the production architecture stack.
  • Generate high-quality renovation and home design layouts using state-of-the-art generative models.
  • Build models that adapt to user feedback and suggest home designs 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.

Desired Qualifications

  • Experience using NumPy and PyTorch is strongly preferred.

About the Company

Dream Technologies

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.

Company size
11-50
Company stage
N/A
Total funding
$60K
Headquarters
Dubai, United Arab Emirates
Founded
2016

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