Artificial intelligence is revolutionizing the world, making its importance felt in every industry. Proportionately, the demand for AI professionals is also rising and by 2024, machine learning jobs are estimated to be worth close to $31 billion.
A strong technical background, varied applied skills and a well-written resume are vital to helping machine learning professionals communicate their expertise and land the job of the future as a Machine Learning Engineer. Since machine learning is at the intersection between data science and software engineering, those who are planning on a career as a Machine Learning Engineer should know how to create algorithms that can sort, optimize and search data. Machine learning engineers also need to have additional machine learning skills in areas such as deep learning, natural language processing and algorithmic optimization.
This article has been penned to provide you with the perfect guideline on how best to build your resume and showcase your skills as a Machine Learning Engineer.
Choose the Right Template
Although machine learning engineers are less concerned about the design of their resumes than creative directors or UI/UX designers, it is important to choose a template. Machine learning resumes that are easy to read and have pleasant aesthetic touches that do not distract from the content are more effective. You can download basic resume templates or use popular word processors to access them. You can also begin by selecting the apt resume template and reaching out to HiCounselor for a second opinion on how to customize or highlight your skills as a Machine Learning Engineer.
Importance of a Well-structured Resume
An effective resume is essential for any job search and every single employer is attracted to a well-structured resume since it helps them quickly assess your eligibility and qualifications for a specific role. So, make sure your resume clearly conveys your value to the organization and also includes the following sections:
Resume Summary:
This section is a brief summary of your personality and accomplishments in three to five sentences. The resume summary is a chance to grab the attention of the hiring manager by providing a compelling narrative. Highlight your strengths and personality here.
Experience:
Your relevant work history should be included in this field. Each experience should be described with a summary of your achievements and responsibilities. Also note the dates and duration of your employment. Include one or two internships relevant to your desired job if you have less experience. Discuss your professional work experience, internships and volunteer work as well. Be sure to connect your past experience to the job requirements if it isn't in machine learning. This could include highlighting desirable soft skills or industry knowledge. If possible, highlight your prior experience with GPU computing and data mining, Apache Spark, agile software development, and the agile process. Knowledge of deep learning and natural language processing (NLP) is also a must.
Projects:
This section summarizes and highlights the relevant projects that you have completed, which may be of interest to prospective employers. It is important to describe the project in detail. Give insight into the problem and your process. You can make up for a lack of work experience by compiling a solid collection of projects. A commendable projects section will demonstrate your technical abilities and critical thinking skills. It will also show your ability to solve real-world business problems. It is important to highlight instances where you have built a prototype and put it into production. You should also create a narrative that explains the problem and your motivations.
Skills:
This field allows you to highlight technical skills that you aren't able to include in the other resume sections. You should mention your ability to use scripting languages such as Java and Python as well as your knowledge of key machine-learning libraries and frameworks such as Scikit-learn and TensorFlow.
Referrals (optional):
This section should contain the contact information of two to three people who are familiar and willing to speak on your behalf. These individuals could be former clients, mentors or instructors. Before you list your references on your resume, ask permission. If your references are not allowed to do so, it can reflect poorly on you.
Education
You might not have any work experience if you are applying for a machine learning position at the entry level. Your resume's education section will fill in any gaps and validate your technical skills. This section can be used to briefly mention your relevant coursework and outstanding academic achievements, regardless of whether you are a boot camp graduate or a Ph.D. This section will list the degrees and courses you have completed. You can add your grade point average if you are an early-career professional as long as it is not less than 3.0.
Present Your Success Stories
Your resume shouldn't become a lengthy list of every job-related responsibility that you have ever held in your past positions. Hiring managers will have a difficult time finding the essential information they need to evaluate your application and make a decision about your hiring. Instead, be proud of the accomplishments and notable projects that you have completed. Your successes should be framed in a way that shows how your achievements will benefit the company. Employers don't care about what you have done, they are interested in what your potential contributions will be. Do not be afraid to brag and describe clearly how your experiences will be a benefit to you in your new role.
When describing prior accomplishments, emphasize outcomes. Demonstrate the positive effects of your past work. How did your project produce results? Did your work improve workplace processes? To show the impact of your work, use performance metrics and other quantifiers. Notify any awards and accolades your projects have received. These will help to confirm the quality of your work.
Reflect Your Skills
Your resume for a Machine Learning Engineer should reflect the skills listed in the job description. Some companies employ automated resume scanning software. You will need to highlight key phrases or skills from the job description in order to pass the initial screen. Although each position will require different skills, there are some common skills that all Machine Learning Engineers should possess. These are some skills employers look for in applicants:
Data structures
Data modeling
Data visualization
Predictive modeling
Statistical modeling
Regression
Classification and clustering
Web scraping
Tensorflow
Pytorch
Keras
Numpy
Pandas
SciKit Learn
MATLAB
Explanatory analysis
Natural Language Processing
PySpark.ML
Jupyter Notebook
Programming languages such as Java and PHP will also be required.
C++
Python
Java
R
Lisp
Prolog
On a final note, avoid the temptation to send a one-size-fits-all resume to every company. Your resume should be tailored to each job that you apply for. Your resume should reflect the specific programming skills required by the job posting. Highlight any certifications you have earned that correspond to the requirements in the job posting. You can highlight past computer vision projects if an employer asks for experience in computer vision.
If you need personalized assistance in building your Machine Learning Engineer Resume, HiCounselor can help you get started on the right track. Click on the link below for unlimited access to HiCounselor’s Resume Builder where you can accelerate your employment search and make use of pre-written examples to pep up your Resume.
HiCounselor has forged technical advances to transform the hiring landscape for job seekers and recruiters alike. Our career accelerator program provides job seekers with coaching and mentorship from industry leaders employed at FAANG companies while recruiters ally with HiCounselor to empower their hiring strategy and hone in on the best candidates. Learn more about HiCounselor here and reach out to us on LinkedIn, Facebook and YouTube.
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