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How to crack interview and get more opportunities?
Hi everyone,
I graduated in Spring 2024 and have been on the job market since then.
I want to get more opportunities for having intro calls.
I want to know the secret to crack interviews for machine learning engineer.
Thank you
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4 answers
Updated
TRAVIS’s Answer
Learn the STAR Interview method and make two resumes. A really long one 4-6 pages with everything you ever did, work, school, volunteer and post on Dice, Linkedin, Careerbuilder, indeed, monster (any resume database) Create a short 1-2 page resume with more relevant and recent experience. Apply to 20-30 jobs day and tailor your resume for each application.
Updated
Jerome’s Answer
I am a huge believer in networking. You would be surprised how many free networking events, and in some cases conferences there are. A fair number of jobs. Still get awarded to people who know people. If there is a way for you to get out of work and meet people, I highly recommend it. You never know where the right connection can lead.
Updated
Wyatt’s Answer
Hello John,
I have over 25 years of experience in the technology sector, having built my career at a high-end technology consulting firm. I began as an engineer and steadily advanced into executive leadership, ultimately overseeing several technology departments and driving strategic initiatives across the organization.
Breaking into the machine learning engineering field requires both strategic visibility and solid technical preparation. To get more opportunities and intro calls, start by making your resume sharp and targeted, focus on real-world ML projects where you applied models, cleaned data, or deployed solutions, and always quantify impact (e.g., “boosted model accuracy by 15%”). Your LinkedIn profile should clearly show you’re open to work, and GitHub should have well documented repositories with readable code and clear README files. Personal projects, Kaggle competitions, or anything deployed via Streamlit or Flask can make you stand out. Don’t underestimate the power of direct outreach. Message engineers or alumni at companies you admire with a short note expressing your interest and linking to a project or resume. Referrals often outperform cold applications. Blogging on Medium, posting on LinkedIn, or contributing to open source projects also increases your visibility and builds credibility in the community.
When it comes to cracking interviews, the key is mastering both the “why” and the “how” of machine learning. You need to go beyond using models to deeply understanding them. Study topics like regularization, loss functions, overfitting, model evaluation metrics, and be able to explain trade-offs. Coding is equally important. Practice Python and focus on Leetcode style problems, especially arrays, hash maps, trees, and dynamic programming. Be prepared to design ML systems and pipelines, discussing things like data preprocessing, feature engineering, model deployment, and monitoring. Interviewers also love digging into your past projects, they’ll want to know what decisions you made and why. Practicing mock interviews, ideally with peers or on platforms like Pramp or Interviewing.io, will help sharpen both your technical and behavioral responses. I would treat job hunting like a full-time job. Target your applications, follow up consistently, and practice until your answers are as strong as your skills.
Wishing you all the best on your exciting journey into the tech world! It’s truly inspiring to see the next generation stepping up and carrying the torch forward.
Wyatt
I have over 25 years of experience in the technology sector, having built my career at a high-end technology consulting firm. I began as an engineer and steadily advanced into executive leadership, ultimately overseeing several technology departments and driving strategic initiatives across the organization.
Breaking into the machine learning engineering field requires both strategic visibility and solid technical preparation. To get more opportunities and intro calls, start by making your resume sharp and targeted, focus on real-world ML projects where you applied models, cleaned data, or deployed solutions, and always quantify impact (e.g., “boosted model accuracy by 15%”). Your LinkedIn profile should clearly show you’re open to work, and GitHub should have well documented repositories with readable code and clear README files. Personal projects, Kaggle competitions, or anything deployed via Streamlit or Flask can make you stand out. Don’t underestimate the power of direct outreach. Message engineers or alumni at companies you admire with a short note expressing your interest and linking to a project or resume. Referrals often outperform cold applications. Blogging on Medium, posting on LinkedIn, or contributing to open source projects also increases your visibility and builds credibility in the community.
When it comes to cracking interviews, the key is mastering both the “why” and the “how” of machine learning. You need to go beyond using models to deeply understanding them. Study topics like regularization, loss functions, overfitting, model evaluation metrics, and be able to explain trade-offs. Coding is equally important. Practice Python and focus on Leetcode style problems, especially arrays, hash maps, trees, and dynamic programming. Be prepared to design ML systems and pipelines, discussing things like data preprocessing, feature engineering, model deployment, and monitoring. Interviewers also love digging into your past projects, they’ll want to know what decisions you made and why. Practicing mock interviews, ideally with peers or on platforms like Pramp or Interviewing.io, will help sharpen both your technical and behavioral responses. I would treat job hunting like a full-time job. Target your applications, follow up consistently, and practice until your answers are as strong as your skills.
Wishing you all the best on your exciting journey into the tech world! It’s truly inspiring to see the next generation stepping up and carrying the torch forward.
Wyatt
James Constantine Frangos
SOFTWARE ENGINEER SINCE 1972; NUTRITIONIST SINCE 1976.
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Answers
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James Constantine’s Answer
Good Day John!
When my uncle died from a heart attack at 38 years of age, I about-faced with my college majors. Physics and mathematics were replaced by biochemistry and nutrition. Then the same thing happened to my father. So, I became a dietitian. How is this relevant to you achieving interview success?
Your performance as a candidate for employment can be increased substantially by nutrient repletion. That is just a fact of life. The secret required for you to crack the code is mental acuity, and enormous intelligence. You can display so much high-level intelligence that it leaves people in awe. Everyone knows that a fast computer or employee is desirable. So long as you do not replace the interviewer, taking their job!
There is no room for pregnant pauses from information technology interviewees when answering questions. The interviewer usually thinks a slow responder - is slow (in finding answers). Fast responses from a qualified Machine Learning Engineer it is what the interviewer shall receive.
SEE https://www.msn.com/en-au/money/career/the-most-common-mistake-jobseekers-make-from-harvard-researchers-and-how-to-avoid-it/ar-AA1xfl1T?
GOD BLESS!
____________________________________________________________________________
When my uncle died from a heart attack at 38 years of age, I about-faced with my college majors. Physics and mathematics were replaced by biochemistry and nutrition. Then the same thing happened to my father. So, I became a dietitian. How is this relevant to you achieving interview success?
Your performance as a candidate for employment can be increased substantially by nutrient repletion. That is just a fact of life. The secret required for you to crack the code is mental acuity, and enormous intelligence. You can display so much high-level intelligence that it leaves people in awe. Everyone knows that a fast computer or employee is desirable. So long as you do not replace the interviewer, taking their job!
There is no room for pregnant pauses from information technology interviewees when answering questions. The interviewer usually thinks a slow responder - is slow (in finding answers). Fast responses from a qualified Machine Learning Engineer it is what the interviewer shall receive.
SEE https://www.msn.com/en-au/money/career/the-most-common-mistake-jobseekers-make-from-harvard-researchers-and-how-to-avoid-it/ar-AA1xfl1T?
GOD BLESS!
____________________________________________________________________________