00:00 Most videos about the life of a machine learning engineer show only the highlights, but the reality is that they spend most of their time behind a desk, working on a computer. 00:59 A typical day for a machine learning engineer involves a morning stand-up meeting with the team, discussing problems and plans for the day. There may also be additional discussions and collaboration with team members on infrastructure and project-related issues. 03:27 The day is usually divided between meetings and coding, with meetings involving discussions with stakeholders about model performance, technical discussions about infrastructure, and planning for future projects. 04:53 The job titles in the field of data can vary greatly, and it's important to understand the different roles and levels of variation within a company before joining. 05:23 The distribution of tasks in a machine learning engineer's day can vary, with a mix of machine learning project work, infrastructure work, support, and meetings. These proportions can fluctuate depending on the stage of a project or other factors. 06:22 Machine learning engineers often work on the same type of ML problem for a long time, focusing on a specific domain or use case. They also work on someone else's code base and tend to settle on specific tools and technologies. 07:51 Documentation is an important part of the job, including writing documentation in Confluence, writing emails and messages, and documenting progress and decisions in JIRA. 08:51 Real-world data is often messy and noisy, requiring a lot of data cleaning and dealing with unexpected issues. Finding clear correlations and solutions can be challenging, and many projects may not have the desired outcome. 10:19 Despite the challenges, being a machine learning engineer is still considered one of the best jobs in the world, but it's important to acknowledge the imperfections and not pretend that everything is perfect.

I was looking for a video about a realistic day to day of AI/ML engineers, thank you!

Came to this video right after wasting 3min on another video just like you described in the beginning. Thank you!

loving the 'slightly more honest' quip Sandro!

these video series are great content. I am coming from an academical background and lucky to had internship on ML/AI and now with your videos I had a chance to get an insight look. Thank you.

What is the value of even trying to solve these real-life problems if, most of the time, there is no solution, no correlation? If my work is not being used, will I risk getting fired?

Extremely helpful, thank you 😊😊

A very true video... Really appreciate it 👍

Please make video on all stages in ml project and tools u use.

Hey, love this video thank you! I noticed at 3 minute 25 seconds the diagram shown has "ML entrepreneur." I have been digging into entrepreneurship/ ML for some time and would like to ask in your day to day roles do you work with external ML solution providers/ entrepreneurs? And what that route would look like. I've always been self employed so really just trying to see if theres a route for ML professionals to be self employed as opposed to working in corporate. Your reply would be much appreciated!

Well, i got invited after entrance test to enroll to University of Oulu for CSE program undergrad + grad and planning on spesializing in AI & ML. Seems like theres many videos to watch now :)

So tough to break into ML tried to land a job for over a year now just given up on it 😔

Hey Sandro, I am looking for a piece of advice. I am a mid level automation QAE in a large company. I want to believe I am pretty technical and in my role I have a lot to do with coding. I’ve been working on transitioning into SDET role, but with AI becoming a the biggest deal in AI I am considering taking a ML bootcamp and trying to land a role as ML SDE. I don’t have a computer science degree and learned everything myself and by working. Do you think it’s realistic to get an ML Engineers role with my background after taking a comprehensive bootcamp?

hey getting offer of engineering AI/DS AND AI/ML what should i choose ??

Do you mentor people? Like one on one mentoring to help those wanting to get into the field?

Can you make a video on MLOps please

Hey can u make a real time project with image classification one? Like dockerzing, using gcp or was for deployment everything?

Hi Maestro, hope you are doing well. I just wanted to ask, if I do masters in computer science...can I have a prospect of becoming ML engineer in the future? P.S. I believe that without becoming a good software engineer, I can't become a good ML engineer. So asked.

Isn't AI engineer and ML engineer seperat major or ther is like mix of them

Hello im currently on my last year of bachelor in cs .i m goodan pythonand its few ml libraries should i focus on learning math and ow to build model or sql, data cleaning andhow to use model please help 1:58

I'm getting my BS in data science currently and will be moving on to get my masters in machine learning. I'm not doing it for all the "fun things" in fact I would dread having to do those things that people consider fun. I'm pursuing this path because I want to sit behind a desk for 6 hours a day (preferably remote work from home) because I've had jobs where I had to wake up at 3 in the morning drag myself to work just to work in the rain at 15 degrees Fahrenheit.

As MLE do you do model building ?

It’s amazing how this video: What professional software engineers ACTUALLY do, kzfaq.info/get/bejne/h5ZxZpiLy83beHU.htmlsi=1GUqy1dK-dzVuHX0 talks about the exact same thing. Exact same words, exact same points … I’m not sure who copied who, but how about being just a tiny bit more creative with the copied content ? 🤦🏾‍♀️