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# Machine Learning Engineer

- **Company:** Rise Technical Recruitment Ltd
- **Location:** San Francisco, CA, United States
- **Salary:** $170,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Computer Programming, Python (Programming Language), Machine Learning, Tensorflow, Pytorch, Deep Learning, Generative AI, Machine Learning Operations, Data Pipelines
- **Published:** July 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=135bb30b664cef21

## About the Role

* US Citizen or Green Card Holder
 * Strong programming skills in Python and machine learning frameworks
 * Experience with PyTorch or similar deep learning frameworks
 * Familiarity with CNNs, Vision Transformers, or diffusion models
 * Experience building or deploying machine learning systems
 * Strong understanding of machine learning fundamentals

## Description

Are you a Machine Learning Engineer looking to work on challenging computer vision and generative AI problems while joining a high-growth AI start-up developing next-generation multimodal technology?

This is an opportunity to join a fast-growing AI company developing next-generation multimodal systems that combine computer vision, generative AI, and large-scale data pipelines. The team works on complex problems involving photorealistic image generation, visual understanding, and multimodal modeling.

In this role, you will develop and optimize machine learning systems across generative and vision-based architectures. You will work closely with research and infrastructure teams to bring advanced AI models from experimentation into scalable production systems.

This role would suit an engineer who enjoys solving complex modeling problems while building production-ready machine learning systems.
The Role:

 * Develop and improve computer vision and generative AI models
 * Optimize diffusion and multimodal ML pipelines for performance
 * Design experiments evaluating visual realism and consistency
 * Deploy scalable machine learning systems into production
 * Collaborate with research and infrastructure teams on model performance


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