Generative AI Interviews (O'Reilly live course) resources

Q: How do we aim for staff level at [tech, AI] companies?

I walked through an example of the career ladder. Dropbox’s engineering ladder happens to be public, and there are other companies whose frameworks are public that you can take inspiration from.

https://dropbox.github.io/dbx-career-framework/ic2_machine_learning_engineer.html

Q: Any recommended resources with projects for Agents, MCP?

Some resources:

• Microsoft’s open source MCP curriculum: https://github.com/microsoft/mcp-for-beginners

• HuggingFace’s Agents course: https://huggingface.co/learn/agents-course/unit0/introduction

• OpenAI tutorial on fine-tuning: https://platform.openai.com/docs/guides/fine-tuning

• Fine-tune your own Llama model tutorial project: https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/2.Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.ipynb

• [Paid] University of Toronto course (from the chat): https://datasciences.utoronto.ca/microcredential_ai/

We’ve also analyzed job postings from the chat. Some interesting findings from this session. I won’t link the exact postings as they will become outdated very quickly:

• The MLE role at Atlassian had a job descriptions that matches more of an MLOps engineer in another job posting at another company.

• Browing Microsoft careers, there were multiple titles, such as Software Engineer - AI Engineer; AI Engineer; Applied AI/ML Engineer. Each of them had respective job descriptions with vastly different responsibilities. Some were more suited for people with more software engineering background with a dash of AI/ML, while many of them required much more AI/ML foundational/ classical skills.

• Cohere had quite a lot of customer facing technical roles, requiring a blend of skills between technical and enterprise customer engineer.
  

One of the biggest benefits of attending this course live is asking questions based on your own situation. We had attendees from vastly different backgrounds, be it more on a DevOps, software, or classical ML, deep learning background, or DS looking to gain more agent experiences.

If you weren’t able to attend this session, you can keep an eye out for future sessions here: https://learning.oreilly.com/live-events/generative-ai-interviews/0636920095524/

Thanks for attending!