What Professional Machine Learning Engineers ACTUALLY Do

Most people will only show you the highlights of their job, today we will look at what professional Machine Learning Engineers actually do in their life.
We will not only look at the many positive things Machine Learning Engineers experience but also the not-so-positive side, and be honest. And I will share many things you don't know about the job and what differences the many data roles may make to this.

If you enjoyed this video, I would be excited to connect on Twitter or LinkedIn.

Intro: 0:00
What is it actually like to be an ML Engineer: 0:30
Not only the positive: 1:15
What your average day will be like: 2:14
Differences between the roles: 4:30
What you don't know about the Job yet: 5:51

[filitico]

loving the 'slightly more honest' quip Sandro!

[Zale]

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.

[uemshow]

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.

[adityaaradhye]

A very true video... Really appreciate it 👍

[jacobsolomon]

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

[MatheusMoraes-ybpb]

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

[dmytrotsanava]

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?

[michaelcoxfitness]

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

[ajinkyapahinkar]

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

[punittheprogrammer]

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

[andracoisbored]

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?

[The_Savolainen]

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 :)

[pratyushpattnaik]

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

[karmadupdhensherpa]

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

[OneWayReality]

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.

[ck-hqiq]

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

[M.I]

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

[bhoyt]

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.

[iMercy_tv]

I’m not sure who copied who, but how about being just a tiny bit more creative with the copied content ? 🤦🏾‍♀️