{"id":2769,"date":"2025-04-01T07:02:20","date_gmt":"2025-04-01T07:02:20","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/04\/01\/my-learning-to-be-hired-again-after-a-year-part-2\/"},"modified":"2025-04-01T07:02:20","modified_gmt":"2025-04-01T07:02:20","slug":"my-learning-to-be-hired-again-after-a-year-part-2","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/04\/01\/my-learning-to-be-hired-again-after-a-year-part-2\/","title":{"rendered":"My Learning to Be Hired Again After a Year\u2026 Part 2"},"content":{"rendered":"

My Learning to Be Hired Again After a Year\u2026 Part 2
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This is the second part of \u201c<\/em>My learning to being hired again after a year\u2026 Part I<\/em><\/a>\u201d<\/em>. <\/p>\n<\/blockquote>\n

Hard to believe<\/mdspan>, but it\u2019s been a full year since I published the first part on TDS. And in that time, something beautiful happened. Every so often, someone would leave a comment, highlight a sentence, or send me a message. Most were simple notes like, \u201cThank you, Amy. Your post helped me.\u201d<\/em> But those words lit me up. They brightened entire days. They reminded me that I was never truly alone, not during those long months of unemployment, not in the struggle of figuring out who I was without a job title or company name beneath my email signature or Linkedin profile.<\/p>\n

Funny enough, those hard days turned out to be some of the most meaningful ones I\u2019ve had. Maybe even more meaningful than my busiest days at work. Because in losing an identity, I found new ones. I didn\u2019t need a job or a title to feel connected. To many of you, I\u2019m just a pretty lazy writer getting back into the groove. And here I am\u200a\u2014\u200areturning to my writing routine. So, thank you to everyone who reached out. Your messages rank second on my list of happiest things people give me. The first? That\u2019s easy. My daughter Ellie\u2019s three S\u2019s: her smell, her smile, and her surprises.<\/p>\n

Enough talk. Let\u2019s get into Part 2. I\u2019ll pick up where I left off \u2014 sharing the lessons that helped me get hired again. This time, I\u2019ll also reflect on how those lessons show up in my work and life today. And for those of you curious about the methods from the book Never Search Alone<\/em>, I\u2019ve got some thoughts on that too. What worked, what didn\u2019t, and how I made it my own.<\/p>\n

Knock, Knock: Opportunity\u2019s at the Door\u200a\u2014\u200aYou Won\u2019t Lose a Penny for Trying<\/strong><\/h2>\n

A year into working as a Machine Learning Engineer<\/a>, I can say this was my biggest life lesson.<\/p>\n

Here\u2019s the backstory. I\u2019d been working as a data scientist ever since I finished grad school. Over the past 7 years, I\u2019ve built multiple machine learning models, linear regression, neural networks and Xgboost. All solid stuff. But when it came to designing an entire machine learning system from start to finish? That was a different story. I hadn\u2019t really done that. I knew how to develop models, sure. I even had some experience deploying them, but only parts of the process. If you asked me to design, build, and run an entire system end-to-end, I couldn\u2019t say I had that experience.<\/p>\n

And the job market? It was changing fast. Companies didn\u2019t want someone who could just build models anymore. Generative AI was handling a lot of the data analysis now. What they really wanted was someone who could take machine learning and use it to solve real business problems, someone who could own the whole process. Meanwhile, I had just been laid off. I had time. So I decided maybe this was the right moment to pivot. Maybe it was time to go for machine learning engineering.<\/p>\n

The first thing I did was reach out to people who had already made that move. Two friends said yes. One had gone from data scientist to machine learning engineer. The other was a data scientist, and her husband worked as an MLE at Apple. We ended up having this long phone call for two hours, maybe more. They were kind. And they didn\u2019t sugarcoat anything. Both of them told me it was tough to make the switch. Not impossible, but tough. If you didn\u2019t have MLOps experience or a solid GitHub portfolio to show off, landing a senior MLE job would be really hard. Especially with how competitive things were getting.<\/p>\n

That conversation hit hard. I remember feeling my heart pound, like cold water had been poured over my head. I had two options: I could keep chasing data scientist jobs\u200a\u2014\u200aapplied scientist roles at places like Amazon\u200a\u2014\u200abut there weren\u2019t many out there. Or swallow my pride, let go of seven years of experience as a data scientist and go for an entry-level MLE role. Honestly, neither choice felt great.<\/p>\n

It took me two weeks to work through it. Two long long weeks. But in the end, I made up my mind: I\u2019d try for machine learning engineer jobs at least, even if I had to start from the bottom. I got back to my routine and prepped for interviews. During those hard days, I started blogging on Medium<\/mdspan> and published on TDS to show my technical muscle, sharing my \u201cCourage to Learn ML<\/em><\/strong><\/a>\u201d series. Ready for a spoiler alert? I ended up with three offers for senior and even staff level machine learning engineering roles. And I had three other final-round interviews lined up that I had to walk away from, because there just wasn\u2019t enough time or energy for me to do them all.<\/p>\n

No, none of those offers came from FAANG companies. But I\u2019m more than happy with where I landed. It was worth the try.<\/p>\n

Even now, writing this, I can still feel that chill from when my friends told me the odds were slim. And I can still laugh at how panicked I was. Just the other day, I spoke with a friend who\u2019s looking to move from data engineering into MLE. I told him the same thing I learned for myself: You can do it. And if you decide it\u2019s worth trying, don\u2019t get hung up on the odds. Even if it\u2019s a 1% chance, why not see if you\u2019re in that 1%? But if you don\u2019t try at all, you\u2019re 100% in the group that never made it.<\/p>\n

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For me, the takeaway is simple. Don\u2019t be afraid of probabilities. Even 99.999999% is not 100%. If you\u2019re worried about the outcome, stop thinking about the outcome. Just do it for fun, for your mental health, for the chance to live without regrets.<\/p>\n<\/blockquote>\n

A Year Later: <\/strong>I use this lesson almost every day. I blog shamelessly, pretending I don\u2019t care about if people really read those. I make those awkward customer service calls, just to see if someone on the other end might actually help me. I even buy a lottery ticket now and then when the jackpot tops a billion dollars. Who knows? I might end up in that 0.0000\u2026001%. And you know what? I recently won $12 on a ticket. So yes\u200a\u2014\u200ait\u2019s worth trying.<\/p>\n

Learning During the Struggle: Don\u2019t Beg for Jobs\u00a0<\/strong><\/h2>\n

This was another hard lesson from my \u201cto be an MLE or not to be\u201d chapter.<\/p>\n

When I spoke with those two friends, they made one thing clear. If I wanted to become a machine learning engineer, I needed hands-on experience with MLOps (machine learning operations). The problem? In my past roles, I\u2019d either handed off my models to software engineers for deployment or handled just one small part of the system myself. I knew I had a gap. And my first instinct was to fill it by any means necessary. So I figured, why not get involved in some real projects? Something complex. Something I could proudly add to my resume.<\/p>\n

Since I was out of work, I had time. I joined MLOps communities on Slack and Discord. I posted about my background, offered to work for free with any startup or team that needed help. Just to get some experience in exchange. The response? Pretty discouraging. Hardly anyone replied. A few did, but they expected me to work 50+ hours a week\u2026 for free and without any working plans. I remember sending a message to a PhD student after reading his job posting. I told him how I liked his work and wanted to make his product a reality. He didn\u2019t get back with me. He instead changed his posting to say he was seeking experienced MLEs or someone with a PhD. Ouch.<\/p>\n

After a few weeks of all that, I was demotivated and burned out. I was pleading for opportunities and it was clear. It was then that I decided to join a Job Search Council (JSC) (I explained JSC in detail in the part 1). We shared the emotional weight of job hunting every Friday. I slowly started letting go of the tension. And that\u2019s when something clicked. I needed to stop pleading for jobs. Instead, I decided to sell what I had.<\/p>\n

I rewrote my resume into two versions, one for data scientist roles and the other for MLE roles. I applied for MLE jobs crazily just to increase the chances. But this time around, I approached it differently. I broke down what the hiring managers were actually looking for in an MLE. I saw how all the model building experience I had acquired had actually taught me on debugging, monitoring, and resolving messy business problems. While I didn\u2019t have a lot of MLOps experience, I wasn\u2019t coming from zero. I had a master\u2019s degree in computer science, I was familiar with software development, and I knew data engineering.<\/p>\n

In those MLE interviews, I started highlighting those skills. I explained how I applied machine learning to solve business problems, offered subtle hints about my favorite model-training tricks. I showed hiring managers I knew how it felt to run systems into production. I was honest about where I needed to gain more experience. But I made it clear this wasn\u2019t a cold start.<\/p>\n

At some point, I stopped acting like a job-beggar and became a salesperson. I wasn\u2019t asking someone to \u201cplease hire me. I\u2019m willing to work more and cheaper\u201d. I was selling something. When a company didn\u2019t hire me, it wasn\u2019t a rejection. It just meant they didn\u2019t need someone like me. Maybe I need to tighten the pitch next time.<\/p>\n

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This mental shift made all the difference. Negative feedback wasn\u2019t personal anymore. It was just feedback, a little data point I could use to make adjustments. When you ask for something, people think less of you. But when you treat yourself as a product, you\u2019re refining and searching for the right buyers. If there\u2019s a flaw, you fix it. If there are good things, you point them out. And sooner or later, you find your people.<\/p>\n<\/blockquote>\n

A Year Later: <\/strong>I don\u2019t beg anymore. Not for jobs. Not for opportunities. I exchange. I sell. That mindset has become part of me now. It\u2019s my inner tiny salesperson.\u00a0<\/p>\n

Mock Interviews and the Interview Marathon: Practice Really Does Make a Difference<\/h2>\n

I\u2019ll be straight with you. Before I started interviewing for machine learning engineer roles after my layoff, I had never really<\/em> practiced behavioral interviews. Not once in my seven years of working. Sure, I wrote out a few stories using the STAR method, like everyone says you should. But I never practiced them out loud, and I definitely never got feedback. It was like stepping on stage to perform in a play without ever going to rehearsal. I never realized how big a mistake that was, probably because, back when the job market was good, I didn\u2019t have to.<\/p>\n

But after the layoff? After spending nearly a year at home because of pregnancy? The market was ice cold. There weren\u2019t many chances, and I couldn\u2019t afford to blow any of them. I had<\/em> to nail the behavioral interviews. Not just by memorizing my stories, but by actually practicing. For real.<\/p>\n

So, I made my husband do mock interviews with me. I sat in one room, he sat in another, and we jumped on Zoom like it was the real thing. Poor guy\u200a\u2014\u200ahe\u2019s been at the same job since forever and works in a totally different field, but there he was, asking me random behavioral questions. At first, I didn\u2019t think it was going to help. I figured he didn\u2019t get what I did anyway. But when I started answering with my \u201cwell-crafted\u201d stories, something surprising happened. I got nervous. And wordy. Way too wordy.<\/p>\n

And then he cut me off. Not gently, either. He told me straight up: I was spending way<\/em> too much time talking about the background. The company, the project, all the setup. He said by the time I got to the part about what I<\/em> actually did, he had already tuned out. You know what? He was 100% correct and I\u2019d never noticed it before. I never thought about how much time I was wasting on details that didn\u2019t really matter to the person listening.<\/p>\n

After that, I went back through my stories. Almost all of them had the same problem. Too much setup, not enough focus on action and results. Honestly? I was grateful for his brutal feedback. It was a little embarrassing, but I wished I\u2019d done mock interviews like that years ago.<\/p>\n

From then on, I decided to practice a lot more. With my new MLE resume ready, I started applying like crazy. Interviews came in, and instead of trying to avoid them, I leaned in. Earlier in my career, I was the kind of person who\u2019d grab the first offer just to escape the stress of interviewing. Selling myself has always made me a little panicky. After all, I\u2019m an introvert. But this time, things were different. The book Never Search Alone<\/em> and those early mock interviews changed my mindset. (I\u2019ll talk more about the book and why it prevents me from rushing out of the interview process later.)<\/p>\n

So I gave myself time. I said yes to almost every interview I could get. At one point, I interviewed with four companies over three days. It felt like a marathon, but somewhere along the way, I got good at telling my story. I watched how the interviewers reacted. I collected feedback from the process. And something strange happened: I stopped caring so much about the results. Whether I got a yes or a no didn\u2019t shake me anymore. I wasn\u2019t just interviewing to get a<\/em> job. I was practicing to get the<\/em> job I really wanted.<\/p>\n

By the time I had three offers on the table and finally chose the one I liked, I knew I was done. That was my finish line. It felt like I\u2019d run the full race and actually won the prize I wanted not the one I settled for.<\/p>\n

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Seriously, I can\u2019t say this enough: KEEP interviewing<\/strong>. Back-to-back if you can. Do mock interviews with whoever you trust, even if they aren\u2019t in your field. Practice until you\u2019re less worried about the outcome and more focused on getting better.<\/p>\n<\/blockquote>\n

A Year Later: <\/strong>It\u2019s hard to say how much of those interview skills I still have in me now. But if I ever need to practice again, you better believe I\u2019ll be dragging my husband back into another round of mock interviews. Maybe even for business presentations. He\u2019s a tough crowd, but he gets results :]<\/p>\n

Panic Mode? Deep Breath, the Show Must Go On<\/strong><\/h2>\n

During my interview marathon, I started noticing something that completely threw me off. Some interviewers looked\u2026 disappointed. Others seemed bored. And me? I cared. A lot. Probably too much. Every time I saw a face that wasn\u2019t smiling or nodding, I panicked. In my head, I\u2019d hear this loud voice saying, \u201cAmy, you\u2019re blowing it.\u201d<\/em> And once that thought crept in, it was over. My brain and body would scramble to fix the situation, so I\u2019d start talking faster, throwing out more words, hoping to change their minds. I wanted to come across as sharp and impressive. But the truth is, I probably looked like a nervous, rambling mess.\u00a0<\/p>\n

My husband confirmed it after one of our mock interviews. He didn\u2019t sugarcoat it. \u201cYou\u2019re not even looking at the camera,\u201d he said. \u201cAnd you seem really tense.\u201d Again, he is the right.<\/p>\n

For an introvert like me, fixing this wasn\u2019t easy. But I found two things that helped. So I will share it here.\u00a0<\/p>\n

The first was simple: breathe<\/strong>. Every time I spotted what I thought<\/em> was a bad reaction, a frown, a yawn, that blank expression that felt like doom, I forced myself to pause. I took a breath. And instead of rushing to say more, I slowed down. Sometimes I even cracked a cold joke. (I\u2019m surprisingly good at bad jokes. It might be my secret talent.) Then I\u2019d apologize for the joke, take another breath, and move on. That little reset worked in two ways. First, it quieted the voice in my head screaming \u201cYou\u2019re ruining this!\u201d<\/em> Secondly, it made the interviewer\u2019s expression change. Maybe they smiled and got the joke. Maybe they just looked confused and didn\u2019t like it. But at least they weren\u2019t bored or disappointed anymore. I\u2019ll take that.<\/p>\n

The second thing I did was tape a picture of my daughter right behind the camera. Her big, shiny smile was right there, and every time I glanced at it, I smiled too. Which, by the way, made me look more relaxed and human on camera. Sometimes the interviewer smiled back, and just like that, the energy shifted. I wasn\u2019t panicking anymore. I was back in control. The show was back on.<\/p>\n

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I started thinking of myself as a salesperson. Or maybe a showman. What do they do when the audience looks tired or distracted? They keep going. They adjust. They bring the energy back. If you\u2019re like me, someone who takes those reactions personally, you need to have a plan. These were my two tricks. You\u2019ll probably find your own. But the point is: don\u2019t panic. Pause. Breathe. No one will notice. And then, get back to the show.<\/p>\n<\/blockquote>\n

A Year Later: <\/strong>Honestly, this might be the most important skill I picked up during that tough year. I still use it all the time at work. When I\u2019m presenting my work to a room full of people, I slow myself down. I picture myself in a fancy tailcoat, like an old-school showman, selling my ideas to the audience. Sometimes I throw in one of my classic cold jokes to keep things light.<\/p>\n

When I wrap up a presentation, I make sure to give people something easy to take with them. I\u2019ll say, \u201cIf you\u2019re heading out and want one thing to remember about this project, here\u2019s the punchline.\u201d<\/em> Then I boil it down to one or two sentences and say it clearly. Loud enough to stick.<\/p>\n

I even use this trick in regular conversations, especially the awkward ones. A little pause makes everything less uncomfortable. And more often than not, things turn out better after that moment to reset.<\/p>\n

Do the Mnookin Two-Pager exercise<\/em>: How I Found a Job That Actually Fit Me<\/h2>\n

I keep mentioning the book Never Search Alone<\/em>, and there\u2019s a reason for that. When I first heard about it, I was skeptical. As an introvert, the idea of joining a group of strangers to talk about job hunting made me extremely uncertain and nervous.\u00a0<\/p>\n

My first group didn\u2019t go well. There were five of us, but two people refused to follow the process. They were often late or skipped meetings entirely. It was frustrating, and I almost gave up. Instead, I found another group through the Slack community. That time, it clicked. We met every Friday, and kept each other accountable. We helped one another stay sane through the search. It made a huge difference. If you want to know more about how the JSC (Job Search Council) helped me, I wrote about it in part one of this story.<\/a><\/p>\n

Looking back, another useful thing the book offered was the Mnookin Two-Pager<\/em> exercise. You sit down and write out what you love in a job, what you hate, and what your career goals are. Simple, but surprisingly powerful. It forced me to get honest with myself. Without it, I probably would have grabbed the very first offer and rushed out of the market, just to be done with it. I\u2019ve done that before. And regretted it.<\/p>\n

This time was different. My two pager list kept me grounded. I knew what I wanted and where I wasn\u2019t willing to settle. That\u2019s how I ended up at Disney. The role hits about 85% of what I was hoping for. More importantly, it steers clear of every red flag on my \u201chard no\u201d list. A year later, I\u2019m still glad I took the time to figure out exactly what I was looking for before saying yes to anything.<\/p>\n

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Finally! We Made It to the End.\u00a0<\/strong><\/p>\n

I\u2019m so glad I finally sat down and finished this. Honestly, I\u2019m the kind of person who thinks a lot. But writing things out like this helps me clear my head and hold on to the lessons I actually want to keep.<\/p>\n

If you\u2019ve enjoyed reading this, and you want to read more stories from me, or you just want to smile at how bad my jokes are, please keep an eye on my posts<\/mdspan> on TDS. Or better yet, subscribe to my newsletter<\/strong><\/a> where I write more frequently about AI and ML, along with life lessons, parenting, and, of course, a few of my cold jokes.! If you\u2019d like to support my writing, you can also just buy me a coffee on https:\/\/ko-fi.com\/amyma101<\/a>! \"\u2615\"\"\u2728\"<\/p>\n

The post My Learning to Be Hired Again After a Year\u2026 Part 2<\/a> appeared first on Towards Data Science<\/a>.<\/p>\n<\/div>\n

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My Learning to Be Hired Again After a Year\u2026 Part 2 This is the second part of \u201cMy learning to being hired again after a year\u2026 Part I\u201d. Hard to believe, but it\u2019s been a full year since I published the first part on TDS. And in that time, something beautiful happened. Every so often, […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,2000,734,1890,240,70,909],"tags":[1014,108,1740],"class_list":["post-2769","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-career-change","category-career-advice","category-data-sciecne","category-editors-pick","category-machine-learning","category-machine-learning-engineer","tag-me","tag-my","tag-part"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/2769"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=2769"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/2769\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=2769"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=2769"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=2769"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}