Google Machine Learning Engineer: 2022 Guide to Bag a Google ML Job

Are machine learning engineers that popular?

With a projected growth rate of 44%, machine learning engineers are set to dominate the job space by 2022. Rightfully so, they played an instrumental role in elevating the integration of technology in mundane daily tasks.

As a machine learning engineer, your primary role would be to create personalized AI tools and algorithms that cater to specific needs. Once they run these tools, it makes carrying out their business objectives much easier!

Machine learning is a subset of a giant circle called Artificial Intelligence. While AI engineers focus on mimicking human behavior, machine learning engineers figure out how to do it. That is, they help computers learn human responses through data.

Being one of the most popular jobs, machine learning engineers have to be at the top of the game to find excellent opportunities. You would have to ensure that you have an application-ready machine learning engineer resume that reflects your expertise!

Here is a summary to give you a headstart:

• There are several career options for machine learning engineers such as Computational Linguist, Data Scientist, Cybersecurity Analyst, etc.
• Google machine learning engineers have superior expertise as they are well-versed with the most contested ML skills and certifications
• Choose the reverse chronological resume format for your Google machine learning engineer resume as it is ATS-friendly
• Structure your resume into distinct sections by evaluating your career history and your target job requirements
• While fresher machine learning engineers perform data modeling, seasoned professionals take up neural networks and natural language processing
• Experienced machine learning professionals must possess technical skills like NumPy, Pandas, Kafka, C++, etc.

Machine learning is an extensive field that will continue to teach you new things every day. Here are a few questions that might be of interest to an enterprising ML professional:

• What does a Google machine learning engineer do?
• How much do machine learning engineers make at Google?
• How do I become a Google AI engineer?
• How do I make a stellar Google machine learning engineer resume?
• Should my machine learning engineer resume have a summary or an objective?
• What skills should I possess as a machine learning engineer?
• How should I draft my professional experience section?

Drafting an excellent machine learning engineer resume can be difficult, which is why we think that our Online Resume Builder will be of great assistance to you! Get a guided explanation of the entire resume-building process with valuable tips.

Here are some related guides that will give you a well-rounded view of the intricacies of machine learning:

• Machine Learning Career
• Machine Learning Engineer
• Machine Learning Jobs
• Machine Learning Interview Questions
• Machine Learning Engineer Salary

Machine Learning Career Options

The field of machine learning hosts a variety of job opportunities. It is a project that requires a professional specializing in each aspect in order to fine-tune the whole process.

Some of the career options for machine learning engineers include:

You can choose your area of interest depending on the functions you prefer performing. If you are interested in protecting the integrity of company data, you could be a cybersecurity analyst. However, if you like handling and structuring data, a data scientist would be your role.

Also Read: List of Machine Learning Jobs

Google Machine Learning Engineer

While it is not impossible, you would have to put extra effort into getting Google machine learning engineer jobs. You could take cloud certifications from Google or build your work experience to be a competent candidate.

Google Machine Learning Engineer Certification

The Professional ML Engineer Certification from Google is one of the most valuable certifications you can hold as a professional. Here are a few topics that this Google machine learning engineer course will cover:

• Framing machine learning problems
• Architect machine learning solutions
• Designing data preparation and processing systems
• Developing machine learning models
• Automate machine learning pipelines
• Monitor and optimize machine learning solutions

To pass this Google machine learning engineer course, you need to attend two online and on-site exams. Such a thorough examining process adds value to this Google cloud certification.

Other certifications similar to the Google machine learning engineer certifications are:

• Professional Certificate Program in Machine Learning & Artificial Intelligence By MIT
• Certificate in Machine Learning By Stanford
• IBM Machine Learning Professional Certificate

Google Machine Learning Engineer Salary

Google machine learning engineer salary stands at the top among other giants like IBM, Netflix, etc.

Here is a compilation of Google machine learning engineer salary from several employment websites:

Also Read: Top machine learning salary trends in 2022

Google Machine Learning Engineer Requirements

Here is a job description to understand Google machine learning engineer requirements:

• Design, develop, test, deploy, maintain and improve ML models/infrastructure and software that uses these models.
• Manage individual project priorities, deadlines, and deliverables.
• Participate in cutting-edge research in artificial intelligence and machine learning applications.
• Build the libraries and frameworks that support large, complex web applications.
• Contribute to engineering efforts from planning and organization to execution and delivery to solve complex, real-world engineering problems.

Google Machine Learning Engineer Interview Questions

You would have to go through an extensive interview process to become a Google machine learning engineer. Divided across various facets is a well-rounded set of interview questions that will evaluate every one of your attributes as an employee.

Every aspiring Google machine learning engineer will go through three interview phases:

• Call with Recruiters
• Technical Round
• On-site Interviews

Call with Recruiters

Recruiters might ask you generic questions like:

• Tell me about yourself
• Why did you choose Google?
• Are you working on any projects? Tell me a bit about it

Make sure that you prepare such common interview questions beforehand so as to avoid stuttering or delay in giving answers. Craft your responses to portray yourself to be the most desirable employee with the right set of soft skills.

Technical Round

You have to show that you have all the right technical skills to fit in at Google. You would have to attend one or two interviews in this round to exhibit your problem-solving/coding skills.

If you are proficient in all of the skills that Google enlisted as required in their job description, you have nothing to worry about!

Practice writing codes without any auto-completion on Google Docs before attending the technical round.

Also Read: What are the top machine learning interview questions?

Optimize Your Machine Learning Engineer Resume

To get a professional-looking resume, it is vital that you organize your details in dedicated sections. The structure of your machine learning engineer resume will matter to the recruiters who have very little time to go through your resume.

Here are some of the formats you can use:

Reverse Chronological Resume Format

You will list your professional experience in this format, starting with the most recent and moving backward. Due to its transparency, it is well-liked by recruiters and software like the applicant tracking system.

However, if you have long career gaps, this resume format may not be the best for you as it will highlight those gaps.

Functional Resume Format

If you are an entry-level professional, changing careers, or have gaps in your employment history, you can opt for the functional resume format that highlights your skill more than your experience.

You can delve into great detail about your skills and correlate them to your suitability for the job. It may not be ATS friendly, but it will complement your unique career trajectory if rightly chosen.

Hybrid Resume Format

Both reverse chronological and functional resume formats may not do justice to your resume separately. In this case, you can use the hybrid resume format.

The hybrid resume format may also not be ATS or recruiter-friendly like the functional format. However, you might as well be honest so that you get a job that is suited to your experience.

Structure Your Resume

Aside from resume formats, your machine learning engineer resume should not be too distracting with various fonts or sections.

While your body can be between the size of 11-12 points, your headings can be 13-14 points in size. Additionally, make sure that you have enough white space and use a margin that does not narrow down your resume too much.

Also Read: Which is the best resume format?

Follow an Outline for Your Machine Learning Engineer Resume

Ideally, your resume should be formatted appropriately into distinct and sensible sections. As a technical position with an astronomical demand, you should do all you can to enhance its readability.

Here is a general guideline of how you can split your machine learning engineer resume:

If you feel like this does not encompass your employment history, you can add more sections to personalize it. For more details on how to add new sections, you can check this guide on Resume Sections to clear your doubts.

However, if you think you're messing up your resume, you can depend on our Online Resume Builder to give you the guidance you need!

Draft an Impactful Summary for Your Machine Learning Engineer Resume

Written at the top of your resume, a resume summary will effectively condense your entire resume into a powerful paragraph.

To make the most of that space, here are a few tips you can follow:

• Start your sentences with power verbs and not I or We
• Avoid over-explaining and keep the sentences concise
• Do not be vague and try to be specific with your work functions
• Maintain a cause-effect relationship
• Cover your most significant achievements

Also Read: How to draft the perfect resume summary

If you are still confused, you can depend on our Online Resume Builder and get valuable suggestions on how you can improve your machine learning engineer resume.

Mention Your Machine Learning Engineer Skills

As a technical profile, you might have a lot of skills to cover in your machine learning engineer resume. In such a situation, you should not be skimping down on your list of skills, instead find a way to include all of them.

The best bet in this situation is to split your skills into two sections:

• Key Skills to list all of your hard and soft skills
• Technical Skills to mention your acquaintance with technical tools

If you are a fresher in the field, the skills section of your machine learning engineer resume would look a lot like this:

• Data Collation & Analysis
• Predictive Modeling
• Dataset Building
• Data Security

As a seasoned professional, your machine learning engineer resume can include the following skills:

• Data Modeling & Evaluation
• Neural Network Architecture
• Natural Language Processing
• Rapid Prototyping

Programming skills are requisite to any technical role, especially machine learning. However, it can be an extensive work environment with a lot of bases to cover.

Here is a broken-down list of which technical skills you should learn based on your expertise level:

Also Read: What skills to put on a resume?

Opt for our Online Resume Builder to help you out with preparing a stellar Google Machine Learning Engineer resume!

Gain Credibility with Projects

One thing that recruiters look for in Google machine learning engineer resumes is the drive for excellence. Since it's a fairly new field with limitless possibilities, doing a few projects aside from Google machine learning engineer courses will be useful.

Create a separate section for projects, be it a college project or independent research. Here is what you can do:

• List your project name
• Include all the technical tools you used by created a tech stack subhead
• Write project details in one-liners and use achievement figures to enhance it
• Add details on the product or service more than other generic factors

If you feel attacked, do not worry. It's not too late to start!

Say you're in high school or in college, here is a guide for beginner machine learning engineer projects you can do.

If you're further up in your career, you may want to dabble in something a bit more revolutionary. A guide on advanced machine learning engineer projects will get your gears turning!

Include Your Professional Experience in Your Machine Learning Engineer Resume

Undoubtedly the focal point of your resume, your work experience section should be updated and on par with industry standards to fare well for you.

Although your professional experience may vary with each person, here is a general overview of what steps you can adopt to do so.

Seasoned Machine Learning Professionals

With a hefty list of work experience, you need to make sure that your machine learning engineer resume is not overburdened with information.

Here is what you can do to ensure that:

• Split your work experience into a bulleted list of one-liners to enhance readability
• Start each one-liner with power verbs for extra impact to the recruiters
• Maintain a cause-effect relationship in every sentence
• Quantify details such as revenue earned, recruits trained, etc.

Doing so will help you make the most of your work experience in your machine learning engineer resume. Additionally, you need to make sure that you follow the reverse chronological resume format to add transparency.

Entry-Level Machine Learning Engineer

If you are a fresher, you would be concerned about your machine learning engineer resume being empty or unappealing.

However, you could elevate it with these tips:

• Write your internships by explaining what you learned and under the assistance of whom, which will explain your cross-functional collaborative skills
• Maintain a cause-effect relationship in each sentence
• If you do not have experience with the target job profile, you can highlight transferable skills to bring out the best of your employment history
• Integrate keywords from the job description into your machine learning engineer resume to efficiently pass the ATS

Also Read: How to present your work experience on resume

Job Preparation Services

At Hiration, we offer all the services that you need to optimize your job hunting process. We can set a guided path for you to follow, by giving you the latest industry standards and rules of thumb.

You can check out our services here:

• Resume Builder
• Cover Letter Builder
• Digital Portfolio Builder
• LinkedIn Review
• Interview Preparation

Key Takeaways

As an enterprising Google machine learning engineer, it is important that you guide all of your hard work in the right direction so that it bears fruition. Here is what you can take away from this definitive article to know more about machine learning:

• You have a range of career options as a machine learning individual, starting from a data scientist to a cloud architect or an AI-systems designer
• A Google machine learning engineer certification will help you gain ample expertise to move up your career ladder
• Opt for the reverse chronological resume format for your machine learning engineer resume as it is preferred by recruiters
• Evaluate your career history and the job requirements enlisted by companies to make sure that your machine learning engineer resume has it all
• Split your machine learning skills into Key Skills and Technical Skills to cover all bases of your knowledge
• Draft a resume summary if you have three or more years of experience by listing all of your major achievements in under five lines

You can drop us a mail at support@hiration.com for any queries or concerns.

Hiration provides you a complete career service platform with 24/7 chat support for all your professional needs from cover letter & resume building, CV, interview preparations, LinkedIn review to building a digital portfolio.