Machine Learning Engineer, Computer Vision

Location: SF - Bay Area / Los Angeles

Role type: Full time

Experience: 5+ years

Role

We're looking for an exceptional Machine Learning Engineer with a strong computer vision

background to join our founding team.

As a founding ML Engineer, you will play a pivotal role in building and shaping the AI capabilities

within our Creator Studio product. Your expertise will be essential in designing and

implementing cutting-edge computer vision capabilities that empower creators with innovative

tools. You'll need to thrive in a fast-paced, dynamic startup environment where you'll wear

multiple hats and have a direct impact on our product's evolution. Ideally, you have a proven

track record of developing and deploying computer vision systems in production, and you're

passionate about pushing the boundaries of what's possible with AI.

Responsibilities

• Develop and deploy state-of-the-art computer vision models to enhance the capabilities
  
  

of our Creator Studio product.

• Research, prototype, and implement new AI features that leverage cutting-edge
  
  

computer vision techniques to solve real-world creator challenges.

• Optimize model performance for speed, accuracy, and scalability, ensuring a seamless
  
  

user experience.

• Collaborate with engineering and design to translate customer requirements into AI
  
  

features and gather user feedback for continuous improvement.

• Contribute to the technical vision and architecture of our AI systems, helping to build a
  
  

scalable and maintainable platform for future growth.

• Stay up-to-date with the latest advancements in computer vision research and evaluate
  
  

their potential applicability to our products.

What you need to have

• 5+ years of experience in industry or an academic setting in developing, evaluating, and
  
  

deploying ML models into production.

Requirements

• Extensive experience in machine learning model development and deployment
• Deep expertise in generative models and large language models
• Strong proficiency in deep learning frameworks and libraries
• Proven ability to scale data pipelines and ML workflows
• Advanced degree in a quantitative field