Machine Learning Ops Engineer At Ai Image-To-Image Startup

What to Expect:

We are seeking a skilled and creative ML Ops Engineer to join our team. As an ML Ops Engineer you will be responsible for utilizing open-source diffusion image generation models to develop high-quality and visually appealing photorealistic images that incorporate the cosmetic medical procedure results. You’ll work alongside our passionate team to help us build our core image generation pipelines for cosmetic procedure simulations. We plan to combine existing libraries with a manual process to implement the solution, leveraging open-source solutions like Stable Diffusion, ControlNet, Dream Booth, and LORA.

We are looking for a candidate with strong with interests in genAI image generation. As part of this role, you will be building the AI workflow for our image generation tool, which utilizes generative AI and computer vision to simulate the post-cosmetic surgery appearance of users — a “try-on” experience for beauty procedures.

Responsibilities:

• Implement and fine-tune open-source stable diffusion image generation models to generate photorealistic images.
• Adapt and enhance existing models to achieve optimal results.
• Explore and experiment with cutting-edge techniques and algorithms to improve image quality and realism.
• Optimize and fine-tune models to enhance performance and efficiency.
• Collaborate with the engineering and design teams to integrate image generation capabilities into a web application.
• Conduct rigorous testing and troubleshooting to identify and resolve any issues or bugs.
• Keep up-to-date with the latest advancements in the field of image generation and deep learning so that we can incorporate all advancements into our workflow.

Qualifications:

• Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field (or equivalent practical experience).
• Strong understanding of deep learning principles, especially in the field of computer vision and image generation.
• Proficiency in working with open-source stable diffusion image generation models, particularly those from Hugging Face and Civitai.
• Solid programming skills in Python, with experience in frameworks such as TensorFlow or PyTorch.
• Experience with deep learning libraries and tools, including CUDA, cuDNN, and GPU programming.
• Familiarity with image processing techniques, algorithms, and tools.
• Ability to analyze, troubleshoot, and optimize deep learning models for performance and efficiency.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

Preferred Qualifications:

• Experience working with generative adversarial networks (GANs) or variational autoencoders (VAEs).
• Knowledge of additional programming languages, such as C++ or Java.
• Experience with version control systems (e.g., Git) and collaborative software development practices.

Join our dynamic team and contribute to cutting-edge advancements in photorealistic image generation. If you are passionate about deep learning and have a keen eye for visual aesthetics, we look forward to receiving your application.