Fall 2024 - Applied AI/ML Engineering Intern

Overview of Role

Heretic Ventures is seeking an Applied AI/ML Engineering Intern for Fall 2024 to support the development of early-stage generative AI consumer businesses that Heretic Ventures is launching.

The ideal candidate is a current student with strong knowledge of Python, experience with generative AI model training and 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).

This is a unique opportunity to help build a billion-dollar company from the ground up while learning from successful repeat entrepreneurs and a stable of powerful and experienced mentors and advisors.

This is a part-time hybrid or remote role, and the position is compensated with salary.

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 and 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 environments, 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.