Five Rules to Follow To Get Your First Role in Tech

amber roberts arize

Amber Roberts

Machine Learning Engineer

The art of landing entry-level tech jobs

Getting your first role in the tech industry can be a time-consuming and difficult challenge. Whether you are a new graduate or are switching into tech from another industry, the challenge is sure to be a rewarding one. Before diving into my five rules to help you navigate this transition, I want to introduce myself. My name is Amber and I’ve helped hundreds of machine learning engineers (MLEs) in the Bay Area, Los Angeles and New York get their first role in tech. While my role now is ML Growth Lead at Arize AI and it is no longer part of my duties to help folks get their next role, I’m proud to offer this guide of distilled lessons.

Let’s get started on the most important rules to follow to make your efforts in role searching as fruitful and efficient as possible.

Rule #1: It’s a numbers game.

I won’t pretend there isn’t a strong sense of irony when new grads aren’t giving themselves a numeric advantage when applying for technical positions. If the likelihood of getting an interview for a cold application (application to a company you have no connections at) is ~1%, that means that you need to apply to 100 jobs / week or 20 jobs a day (Mon–Fri) to get an interview on the calendar. The irony also isn’t lost on prospective machine learning engineers (MLEs) whose resumes are being filtered out by a ML algorithm. We know the general rules and template of a tech resume (1-page and ONLY 1), but how do we get that resume circulated and passed through the algorithm at tech companies? Projects. Keywords. Volume.

Here are some simple rules I live by for submitting cold job applications:

  • Again, one-page – I mean it.
  • Few read cover letters. I’m 99% convinced by this if they are a large company. Even if your cover letter is read by a human, it will not make or break you getting the interview. Write a generic cover letter with a few specific details if it’s a requirement.
  • Do not prepare for the interview until you get an interview. Should you prepare for general tech and phone screen interviews in the meantime? Yes, but you do not need to know any company’s mission statement by heart.
  • Meet at least 50% of the job requirements.
  • Make sure the important parts of the job requirements that you have experience with are in your resume. This can even be word for word, the algorithm will love it! You can take out the Kaggle competition when needed.
  • Don’t over-embellish. Tech is small, be authentic, and don’t oversell your skills – but be confident in the transferable skills you have (more on this in Rule #5).
  • Apply on LinkedIn via one-click-applying after filtering on date added (most recent to least recent). Not enough emphasis is placed on volume with most new grads, increasing your number of applications with recent and relevant job postings will help.

Of course, all of this is secondary if you have a connection at a company (warm introduction). If you know someone willing to refer your resume to their internal team, your odds of getting through to the first round of interviews increases by an order of magnitude. Now, exactly how do we get your resume introduced?

Rule #2: Network. Network. Network.

People are always surprised when I tell them my network has gotten me more opportunities than my masters degree. The truth is that a strong, robust network can open doors that your education cannot. Let’s compare and contrast an advanced degree with an advanced network.


  • Both put you outside your comfort zone
  • Both are hard to get
  • Both increase your opportunities


  • Networking continues past three years
  • Networking provides you insights outside of your domain
  • Networking gives you as much out of it as you put in

Building a network is a marathon, not a sprint. Even if you are in school or another role now there are plenty of ways to start building your network on LinkedIn. My favorites are: free virtual events (workshops, conferences, panels, and talks), in-person tech meetups, or even just reaching out to authors of research papers and medium posts after enjoying them.

Here are some examples of how to reach out to folks on LinkedIn who you would like to connect with:

Option 1: Building my network full of like minded people

Hello Amber,

I saw that you are a speaker for the Arize:Observe LLMOps learning event and I would like to connect. I am a graduate student at Hogwarts completing a master’s degree in Machine Learning for Muggles. Thank you for connecting.

Option 2: Targeted search from event

Hello Amber,

I saw your talk at the Arize:Observe LLMOps Learning event and I would like to connect. I am a graduate student at Hogwarts completing a master’s degree in Machine Learning for Muggles and saw that Arize has an open MLE role. Would you mind if I ask you a few questions about your role and your experience with Arize? Thank you!

Option 3: Targeted search from job posting

Hello Amber,

I’m also Amber, a graduate student at Hogwarts completing a master’s degree in Machine Learning for Muggles and saw that Arize has an open MLE role [LINK TO ROLE , if you can]. Would you mind if I ask you a few questions about your role (ONLY IF IT’S THE SAME ROLE) and(OR) your experience with Arize? Btw, I read your latest blog post on Algorithms and Potions (DO YOU RESEARCH) and found it very informative. Thank you!

Note that these are just a few examples that sound like me, you should add your own personality to these if you can. Also, if you are from the same place, went to the same school, worked at the same company, or have mutual connections, mention that in the note to form a better connection. Now, I know for a lot of folks this is being pushed outside of your comfort zone, but you need to take more chances to increase your odds of getting a job. Remember, it’s still a numbers game. What’s the worst that could happen? They could not respond or say “no,” but I know from experience those are not the thoughts running through their heads if they are not burned out.

What am I thinking when I get reached out to like this?

  • 10 minute call? Sure, I’m happy to chat, I’ve been in that same position.
  • Machine learning advice? I actually have learned a lot over the last 5 years and have experience I wish I knew at the beginning of my journey.
  • If I like them and can see them as a co-worker, that would mean less work on my plate if they get hired (plus a referral bonus depending on your employer)…
  • No harm, harm no foul. If the 10 minutes aren’t that useful to either of us at least I made a new connection and expanded my network.

Rule #3: If it’s never the right time, it’s always the right time.

The Arize Community Slack channel is full of first-time graduates who are looking for their first role in tech. After having chatted with many of these individuals, I hear a very commonly repeated sentence: “it’s not the right time, companies aren’t hiring.” While it is important to keep in mind that job market conditions can vary significantly by location and industry, I can say that I have heard from new grads that “it’s not the right time” each year since I have graduated. Notably, I’m less likely to hear this statement from individuals who are changing fields, likely because they have gone through several periods of difficult hiring due to economic conditions.

The facts are that over the past 15 years, the U.S. job market has fluctuated in ways that impact the tech industry, as well as the job market for new grads. Here are some years that were considered challenging for new grads to find jobs:

  • 2008-2009: The Great Recession began in late 2007 and lasted until mid-2009, leading to widespread job losses and hiring freezes across many industries.
  • 2010-2011: While the economy was recovering from the recession, unemployment remained high and job growth was slow. This made it difficult for new grads to find entry-level positions.
  • 2016-2017: The job market was recovering from the Great Recession, but growth was slow and some industries were still struggling to hire new workers.
  • 2019: While the overall job market was relatively strong, some industries experienced a slowdown in hiring, such as retail and manufacturing.
  • 2020: The COVID-19 pandemic caused widespread disruption in the job market, leading to high levels of unemployment and hiring freezes across many industries.

We can see that having an ideal year for being hired is like flipping a coin, yet the data scientist role has grown over 650% since 2012. Year after year more candidates are being hired in tech, from senior to entry level positions. So if the number of roles in the tech industry is growing, and the advancements and capabilities in technology are only accelerating, don’t be afraid to start.

Rule #4: If it can change, it will change.

In tech the only consistent skill is the skill to learn new skills quickly. The tech environment and toolchain landscapes are constantly advancing accordingly, the skills required and desired for new and in-demand roles are changing as well. As some job titles become obsolete, new titles are being created. For example, we have had our first Prompt Engineering roles hired for only this year! While the titles aren’t consistent, growth in the tech space is only accelerating year after year.

Even when companies see hiring slow down, there are still certain roles that need backfilled and new roles that need added. Over the past 12 months, Turing reported over 900,000 job postings for software developer/engineer positions in technical roles and on average, a hiring manager takes 43 days to fill each position.

top tech jobs by growth

While the hiring for the role of data scientist may be decelerating, it is not going away anytime soon. Insiders in the tech space are seeking certain engineering capabilities not necessarily encapsulated by the term “data science.” Essentially, there’s an enterprise demand for talented people who know how to build robust systems and get data science to actually work in production. This means hiring engineers with applied skills who can manage models at scale, not just making it work with training data inside a Jupyter notebook. Now, those roles (big data engineer, data engineer, backend engineer, DevOps engineer, etc.) have always been desired technical hires and in-demand roles, but today’s companies have more data than ever and there are more large ML models in production than there ever have been. Similarly to when companies started to hire their first cloud engineers, there is a correctional shift in the market based on the current needs of companies.

Rule #5: Everything is an interview – but not in the way you might think.

We talked about how to get an interview on your calendar – numbers and networks – but what do you do to prepare for it? Once again, there are a set of rules to live by when starting the interview process.

  1. Ask the person who is coordinating the interview if there’s any material he or she could provide you for the process of the interview. Most of the time teams will tell you the exact format of the interview process and content of the interview. You can ask as many reasonable questions as you like until they tell you that “this is all the information we can offer.” You can ask if the coding interview will be a paired coding problem, if it will be a debugging challenge, what software it uses and how long it should take to complete. Again, the worst thing they can say is “no, we can’t provide that.”
  2. Before starting any interview, what is the one thing the interviewer wants from a candidate? Hands down, it is the ability to hire you and stop having to interview for that position. Keep that in mind, the interviewer is on your side 99% of the time (the other 1% means a red flag and you don’t want to work there anyway).
  3. The tech screen. This is a conversation, try to have the interviewer talking as much as possible. Remember they are on your side and will give you as much detail as they can so that you get to the right answer together. Include them in your thought process and reasoning. Even if you end up getting the question wrong, or not getting to the answer, if the interviewer can see you as a teammate it doesn’t mean you failed.
  4. The onsite.
    • The onsite can be up to two weeks after your last interview, but don’t push it back further than that unless there is an emergency, you don’t want to lose the opportunity.
    • Get to know everyone, ask questions, remember you are interviewing them as well. Ask questions about their career progress, the company, their managers, their goals and work life balance.
  5. The post-interview.
    • After every interview, in every stage, send each interviewer a message on email or LinkedIn – I prefer LinkedIn because it builds those connections – thanking them for their time.
    • Pro tip: If in a technical interview, if you don’t have enough time to finish the problem, write down how you would have solved the problem and send it to them. This never hurt a candidate’s chances in my book, in fact it improved them.
  6. You got the offer?
    • Great, now it’s time to negotiate! Remember this is the point in time where you will have the most leverage to ask for what you want and what you feel like you deserve. Negotiating can be an entire additional blog post, but just remember you can negotiate on: your base salary, signing bonus, equity or stocks, work from home days, relocation bonus, vacation, even who you would prefer your manager to be and what you expect down the line.
  7. You didn’t get the offer?
    • I know it stings, but use this as an opportunity to improve yourself. Ask the interviewers for feedback so that you can improve your interviewing skills for the next role. Also, let the interviewers who you connect with know that you hope to work with them sometime in the future, chances are they will keep you in mind.


I have seen these five rules work incredibly well for new grads and professionals looking to switch careers into tech. Understand that the first role is by far the hardest to get; after having a few years of experience, future roles become easier to achieve. This is due to the confidence you gain from being in the field, the network you have developed, and because the algorithm loves to see that experience on your resume.

Since we talked a lot about networking and numbers, the last thing I want to convey about getting that next role is knowing your worth. You should be trying out different roles, learning new skills and finding out what makes you a unique candidate. As new roles are added to the industry and old ones are made redundant, you need to develop the confidence that you can adapt by knowing your worth and owning your skills. Change in life is inevitable and change in tech already happened while you read this article. Best of luck; you got this!