ML Engineer - Generative AI

Dream Technologies; San Francisco (CA); On-site; USD 110,000 - 150,000; Full time

Job summary

A leading tech company in San Francisco is seeking a Generative AI engineer to develop novel spatial generative AI models. Responsibilities include generating high-quality design layouts, adapting models based on user feedback, and deploying solutions in production. The ideal candidate holds a Master's degree in Computer Science, has over 2 years of real-world AI experience, and is proficient in Python, particularly with NumPy and PyTorch. Creativity and a strong mathematical background are essential.

Qualifications

• 2+ years of experience training and deploying real-world AI.
• Deep understanding of model architectures, training pipelines, and evaluation methodologies.
• Ability to design performant solutions to spatial and generative problems.

Responsibilities

• Generate high-quality renovation and home design layouts.
• Build a model that adapts to user feedback.
• Define required datasets and work with labeling agencies.
• Deploy models to production environments and iterate based on user feedback.

Skills

Proficiency in Python

Experience with NumPy

Experience with PyTorch

Creativity in machine learning approaches

Strong background in algorithms and data structures

Education

MS in Computer Science with a focus on Machine Learning

Job description

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.