Machine Learning Engineer CV example

You’re a master of machine learning and you’re ready for your next engineering role.

You need to create a standout CV that’s going to grab the recruiter’s attention and secure you an interview.

So, to help you produce an impressive application, we’ve put together our expert writing guide, along with a machine learning engineer CV example below.

 

 

 

Machine Learning Engineer CV example

Machine Learning Engineer CV 1

Machine Learning Engineer CV 2

 

This CV example showcases the optimal structure and format for your Machine Learning Engineer CV, providing a pleasant reading experience for busy recruiters.

It also demonstrates the skills, experience and qualifications you should emphasize in your own CV to increase your chances of landing job interviews.

 

CV builder

 

Machine Learning Engineer CV format and structure

Your CV is the first impression you’ll make on anybody who reads it.

A disorganised, cluttered and barely-readable CV could seriously decrease your chances of landing interviews, so it’s essential to make sure yours is slick, professional and easy to navigate.

You can do this by using a clear structure and formatting your content with some savvy formatting techniques – check them out below:

 

How to write a CV

 

Tips for formatting your Machine Learning Engineer CV

  • Length: If you want to hold the reader’s attention and ensure your CV isn’t yawn-worthy, it’s best to stick to two sides of A4 or less. This is more than enough room to highlight why you’re a good match for the role – anything more can quickly become tedious!
  • Readability: By clearly formatting your section headings (bold, or a different colour font, do the trick) and breaking up big chunks of text into snappy bullet points, time-strapped recruiters will be able to skim through your CV with ease.
  • Design & format: While it’s okay to add your own spin to your CV, avoid overdoing the design. If you go for something elaborate, you might end up frustrating recruiters who, above anything, value simplicity and clarity.
  • Photos: Don’t add profile photos to your CV unless you work in an industry or region which prefers to see them. Most employers in the UK will not need to see one.

 

Quick tip: Creating a professional CV style can be difficult and time-consuming when using Microsoft Word or Google Docs. To create a winning CV quickly, try our quick-and-easy CV Builder and use one of their eye-catching professional CV templates.

 

CV formatting tips

 

 

CV structure

As you write your CV, divide and sub-head into the following sections:

  • Name and contact details – Always start with these, so employers know exactly how to get in touch with you.
  • CV profile – Add a short summary of your relevant experience, skills and achievements, which highlights your suitability.
  • Core skills section – A 2-3 columned list of your key skills.
  • Work experience – A detailed list of any relevant work experience, whether paid or voluntary.
  • Education – An overview of your academic background and any training you may have completed.
  • Hobbies and interests – A brief overview of your hobbies and interests, if they’re relevant (optional).

Now you understand the basic layout of a CV, here’s what you should include in each section of yours.

 

Contact Details

Contact details

 

Make it easy for recruiters to get in touch, by heading your CV with your contact details.

There’s no need for excessive details – just list the basics:

  • Mobile number
  • Email address – Use a professional address with no nicknames.
  • Location – Just write your general location, such as ‘London’ or ‘Cardiff’ – there’s no need to put your full address.
  • LinkedIn profile or portfolio URL

 

Machine Learning Engineer CV Profile

Make a strong first impression with recruiters by starting your CV with an impactful profile (or personal statement for junior applicants).

This short introduction paragraph should summarise your skills, experience, and knowledge, highlighting your suitability for the job.

It should be compelling enough to encourage recruiters to read through the rest of your CV.

 

CV profile

 

How to write a good CV profile:

  • Make it short and sharp: It might be tempting to submit a page-long CV profile, but recruiters won’t have the time to read it. To ensure every word gets read, it’s best to include high-level information only; sticking to a length of 3-5 lines.
  • Tailor it: Recruiters can spot a generic, mass-produced CV at a glance – and they certainly won’t be impressed! Before you write your profile (and CV as a whole), read through the job advert and make a list of any skills, knowledge and experience required. You should then incorporate your findings throughout your profile and the rest of your CV.
  • Don’t add an objective: If you want to discuss your career objectives, save them for your cover letter, rather than wasting valuable CV profile space.
  • Avoid generic phrases: Clichés like “blue-sky thinker with a go-getter attitude” might sound impressive to you, but they don’t actually tell the recruiter much about you. Concentrate on highlighting hard facts and skills, as recruiters are more likely to take these on board.

 

Example CV profile for Machine Learning Engineer

Motivated Machine Learning Engineer with 10+ years of success in REST API development and implementing AI-driven solutions that have a profound impact on numerous industries, from healthcare, telecoms, and finance to e-commerce and autonomous vehicles. Passionate about contributing to innovation R&D projects aimed at driving automation and technology integrations. Proven ability to work independently and with a team to meet deadlines in fast-paced settings.

 

What to include in your Machine Learning Engineer CV profile?

  • Experience overview: To give employers an idea of your capabilities, show them your track record by giving an overview of the types of companies you have worked for in the past and the roles you have carried out for previous employers – but keep it high level and save the details for your experience section.
  • Targeted skills: Make your most relevant Machine Learning Engineer key skills clear in your profile. These should be tailored to the specific role you’re applying for – so make sure to check the job description first, and aim to match their requirements as closely as you can.
  • Important qualifications: If the jobs you are applying to require candidates to have certain qualifications, then you must add them in your profile to ensure they are seen by hiring managers.

 

Quick tip: If you are finding it difficult to write an attention-grabbing CV profile, choose from hundreds of pre-written profiles across all industries, and add one to your CV with one click in our quick-and-easy CV Builder. All profiles are written by recruitment experts and easily tailored to suit your unique skillset.

 

Core skills section

In addition to your CV profile, your core skills section provides an easily digestible snapshot of your skills – perfect for grabbing the attention of busy hiring managers.

As Machine Learning Engineer jobs might receive a huge pile of applications, this is a great way to stand out and show off your suitability for the role.

It should be made up of 2-3 columns of bullet points and be made up of skills that are highly relevant to the jobs you are targeting.

 

Core skills section CV

 

Important skills for your Machine Learning Engineer CV

Programming Languages – Maintaining proficiency in programming languages commonly used in machine learning, such as Python and R, for developing and implementing algorithms and models.

Machine Learning Libraries – Maintaining expertise in machine learning libraries and frameworks like TensorFlow, PyTorch, or scikit-learn for building and training machine learning models.

Statistical Analysis – Using statistical techniques and methodologies to analyse data, make data-driven decisions, and select appropriate machine learning algorithms.

Data Preprocessing – Completing data preprocessing tasks, including data cleaning, feature engineering, and handling missing or noisy data to prepare datasets for model training.

Deep Learning – Maintaining familiarity with deep learning concepts, architectures, and frameworks for tasks such as image recognition, natural language processing, and neural network design.

Model Evaluation – Using evaluation metrics like accuracy, precision, recall, F1-score, and ROC-AUC to assess the performance of machine learning models.

Big Data Technologies – Utilising knowledge of big data technologies like Hadoop, Spark, or Databricks for handling and processing large datasets efficiently.

Cloud Platforms – Using cloud platforms like AWS, Asure, or Google Cloud for deploying, scaling, and managing machine learning models in the cloud.

Version Control – Using version control systems like Git to manage and track changes in machine learning code and collaborate with team members.

Deployment and Productionisation – Deploying machine learning models into production environments, containerising models, and integrating them into web applications or data pipelines.

 

Quick tip: Our quick-and-easy CV Builder has thousands of in-demand skills for all industries and professions, that can be added to your CV in seconds – This will save you time and ensure you get noticed by recruiters.

 

CV builder

 

Work experience

By this point, employers will be keen to know more detail about you career history.

Starting with your most recent role and working backwards, create a snappy list of any relevant roles you’ve held.

This could be freelance, voluntary, part-time or temporary jobs too. Anything that’s relevant to your target role is well-worth listing!

 
Work experience
 

Structuring each job

Lengthy, unbroken chunks of text is a recruiters worst nightmare, but your work experience section can easily end up looking like that if you are not careful.

To avoid this, use my tried-and-tested 3-step structure, as illustrated below:

 
Role descriptions
 

Outline

Start with a brief summary of your role as a whole, as well as the type of company you worked for.

 

Key responsibilities

Use bullet points to detail the key responsibilities of your role, highlighting hard skills, software and knowledge wherever you can.

Keep them short and sharp to make them easily digestible by readers.

 

Key achievements

Round up each role by listing 1-3 key achievements, accomplishments or results.

Wherever possible, quantify them using hard facts and figures, as this really helps to prove your value.

 

Sample job description for Machine Learning Engineer CV

Outline

Build and deploy machine learning frameworks that enable multi-sector businesses to leverage data for various purposes, for company that helps 130K+ organisations connect better through voice, video conferencing, chat, contact centre, and file sharing

Key Responsibilities

  • Select appropriate architectures for specific tasks, such as classification, regression, clustering, or recommendation systems.
  • Gather, clean, and pre-process large datasets for extensive model training.
  • Perform comprehensive exploration and feature engineering to extract meaningful information from raw data.
  • Write formulas, including supervised, semi, and unsupervised techniques, while maintain code for pipelines and workflows.

 

Quick tip: Create impressive job descriptions easily in our quick-and-easy CV Builder by adding pre-written job phrases for every industry and career stage.

 

 

Education section

At the bottom of your CV is your full education section. You can list your formal academic qualifications, such as:

  • Degree
  • GCSE’s
  • A levels

As well as any specific Machine Learning Engineer qualifications that are essential to the jobs you are applying for. Note down the name of the qualification, the organisation at which you studied, and the date of completion.

 

Hobbies and interests

This section is entirely optional, so you’ll have to use your own judgement to figure out if it’s worth including.

If your hobbies and interests could make you appear more suitable for your dream job, then they are definitely worth adding.

Interests which are related to the industry, or hobbies like sports teams or volunteering, which display valuable transferable skills might be worth including.

 

CV builder

 

Once you’ve written your Machine Learning Engineer CV, you should proofread it several times to ensure that there are no typos or grammatical errors.

With a tailored punchy profile that showcases your relevant experience and skills, paired with well-structured role descriptions, you’ll be able to impress employers and land interviews.

Good luck with your next job application!