How to apply for Applied AI Data Scientist (Brazil)

About AE Studio

AE Studio is a software company that provides product design, software development, machine learning, and data science services. It builds products, platforms, and internal ventures that increase agency for all conscious beings. The company combines software engineering, AI expertise, and product design to ship ambitious projects, and it also pursues AI alignment research.

About the role

As an Applied AI Data Scientist, you will split your time between client projects and internal research initiatives. You will build data-driven solutions, use machine learning models, and contribute to AI alignment research. You can also propose and pursue high-impact research projects, which may become prioritized skunkworks initiatives.

A typical day

A typical day might involve working on a client project to build a data-driven solution, then switching to an internal research initiative on AI alignment. You could also spend time designing prompts, testing LLM techniques, or proposing a new research project. Since the role is remote, you would collaborate with a distributed team and manage your own schedule.

Who AE Studio is looking for

• Has fluency in Python.
• Has experience with the full LLM lifecycle: prompt design and engineering, prompting techniques such as RAG, few-shot, and CoT, vector databases, multimodality, and fine-tuning.
• Is adaptable, collaborative, and enjoys solving challenging problems independently and with a team.
• Brings creativity and humor to work, and is excited to push boundaries in AI and data science.

Tips for this application

• Highlight specific projects where you used Python and worked with LLMs, including prompt design, RAG, few-shot, CoT, vector databases, multimodality, or fine-tuning.
• Show how your work increased agency for users or systems, since AE Studio's mission is to increase agency for all conscious beings.
• Mention any experience with AI alignment research or internal research initiatives, as the role includes contributing to groundbreaking AI alignment research.
• Explain your ability to work on both client projects and internal research, and give examples of adapting to different problem types.
• If you have proposed or led research projects, describe them and note if they became prioritized initiatives, since AE Studio values high-impact research proposals.

What to cover in your cover letter

Emphasize your Python fluency and hands-on LLM lifecycle experience, including prompt engineering, RAG, few-shot, CoT, vector databases, multimodality, and fine-tuning. Describe how you have solved real-world problems with data-driven solutions and machine learning models. Explain your interest in AI alignment research and how you could contribute to AE Studio's mission of increasing agency. Show that you can work independently and collaboratively on both client projects and internal research.

Research before applying

• Read AE Studio's website, especially the about page and any pages on AI alignment research, to understand their mission and services.
• Look for public information on AE Studio's client projects and internal ventures to see the types of products and platforms they build.
• Search for AE Studio's research publications or blog posts on AI alignment and data science to understand their research direction.
• Check if AE Studio has open-source projects or GitHub repositories related to LLMs, data science, or AI alignment.

Likely interview topics

Based on the job description, expect questions about:

• Walk through a project where you used Python and LLMs, including prompt design and techniques like RAG, few-shot, or CoT.
• How would you approach building a data-driven solution for a client project at AE Studio?
• Describe your experience with vector databases, multimodality, or fine-tuning in LLM applications.
• What high-impact research project would you propose to increase agency, and how would you pursue it?
• How do you balance client work with internal research initiatives in a remote environment?

Common mistakes to avoid

• Applying without demonstrating specific experience with LLM lifecycle components like prompt design, RAG, few-shot, CoT, vector databases, multimodality, or fine-tuning.
• Ignoring AE Studio's mission of increasing agency for all conscious beings and not connecting your work to that goal.
• Submitting a generic application that does not address the mix of client projects and internal research, or the possibility of proposing skunkworks initiatives.