Researching Real Job Requirements

00:00 Now that you’ve chosen a developer path, you’ll need to answer one simple question. What does the job market actually reward right now? And to understand that, you’ll have to do a little bit of research.

00:12 Open any job search platform like Indeed or LinkedIn in your browser. So here you can see that I have Indeed open. And let’s say that you’re interested in machine learning engineer positions. So you open five to 10 current job listings about machine learning engineer positions, but you could also be interested in the role of Python developer, backend engineer, data analyst, QA automation. So as you read through this job ad, you’ll start highlighting the technical requirements that appear repeatedly. So if you’re looking at machine learning job ads, you’ll quickly start finding that they ask for proficiency in Python, R or C++, PyTorch, TensorFlow, or other machine learning frameworks.

01:01 As you do this research, you’ll quickly start to notice patterns. For web development roles, they often emphasize frameworks like Flask, Django, FastAPI, along with database knowledge, REST API design, and also JavaScript, HTML, and CSS.

01:19 For data science positions, they usually require libraries like NumPy, pandas, Polars, and Matplotlib, and also an understanding of statistical concepts.

01:31 For machine learning jobs, they usually also ask for PyTorch or TensorFlow, and for test automation roles, they likely require familiarity with frameworks such as Selenium, Playwright, or Scrapy.

01:44 And even though the requirements for these roles look different, they all share the same core. Almost every job expects you to understand Python fundamentals deeply, to know how to use version control systems like Git, and to be able to write your unit tests and debug problems systematically.

02:07 And it’s usually considered a plus when you have familiarity with DevOps practices and cloud platforms. These concepts matter as much as knowing any specific framework. Lately, job postings also expect familiarity with AI coding tools like GitHub Copilot, Gemini CLI, Cursor, Claude Code, or Codex.

02:32 Employers want developers who can use these AI tools productively, but also to keep judgment and review and validate AI-generated code.

02:43 Because nowadays AI tools are handling the more routine coding tasks, employers are highly interested in developers who can think at the system level. That means understanding how components fit together, designing scalable architectures, and making trade-offs between approaches.

03:01 The reason why these system design skills are harder to outsource through the AI is because they require judgment and knowledge about the business requirements, the user needs, and long-term maintainability.

03:14 In the next lesson, you’ll take a moment to reflect on your findings and preferences to choose the best path for you.