Spring Semester - Applied AI/ML Engineering Intern

Location: San Francisco with the ability to visit our office one day a week.
About Arcade
Arcade is the world’s first AI product marketplace, enabling anyone to design, purchase, and sell custom, manufacturable products with a simple text prompt. Co-founded by Mariam Naficy, Arcade brings together the power of generative AI with a global network of top artisans to turn user ideas into personalized, physical products. Arcade aims to redefine commerce by offering unprecedented personal choice, expression, and meaning in product creation.Arcade is incubated by Heretic Ventures and is backed by investors such as Offline Ventures, Sound Ventures, and Reid Hoffman.
Overview of Role
Arcade  is seeking a Spring Semester intern for our ML/AI engineering team. 
This is a unique opportunity to contribute to a breakthrough company from the ground up while learning from successful repeat entrepreneurs and a team of powerful and experienced mentors and advisors. 
The ideal candidate is a current student who has strong knowledge of Python, experience with generative AI model training & fine-tuning, and has worked in professional environments with engineering or AI/ML teams.  This engineering intern will participate in the full end to end deep learning pipeline from data collection to model deployment. You'll wear many hats, but your primary focus will be on making our AI models better (and defining what better means by setting up amazing evaluation metrics).

Responsibilities

• Collaborate with cross-functional teams to train and fine-tune machine learning models and systems for consumer-focused ventures.
• Build machine learning models  for various generative AI applications, including text-to-image diffusion models, large language models, and other emerging generative AI.
• Develop multi-model architectures to meet product & business requirements for new venture concepts.
• Collect, preprocess, and analyze data to extract meaningful insights and improve the performance of AI models.
• Deploy and maintain AI models in production environments, ensuring scalability, reliability, and efficiency.
• Stay up-to-date with the latest advancements in AI technologies, contribute to research environment, and apply them to enhance the performance and capabilities of our ventures.
• Communicate complex AI concepts and solutions effectively to both technical and non-technical stakeholders.

Qualifications

• Currently enrolled in a Bachelor's, Master's, or PhD degree in Computer Science, Mathematics,  Artificial Intelligence / Machine Learning, or a related field.
• Prior professional experience working on applied AI projects, preferably in a product development or research environment.
• Strong knowledge of Python and familiarity with Linux with experience in popular machine learning libraries (e.g., TensorFlow, PyTorch).
• Solid understanding of machine learning concepts and algorithms.
• Experience with training and fine-tuning AI models and working with large-scale datasets.
• Proficiency in data preprocessing, feature engineering, and exploratory data analysis.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and experience with deploying AI models in cloud-based environments.
• Excellent problem-solving and analytical thinking skills, with a strong attention to detail.
• Effective communication and teamwork abilities, with the capacity to work in a fast-paced, collaborative environment.

Nice to Haves

• Experience fine-tuning Stable Diffusion models for specific product use cases.
• Experience fine-tuning OpenAI GPT models for specific product use cases.
• Contributions to open-source AI projects or publications in relevant conferences or journals.