How to Write a Machine Learning Engineer CV: Step-by-Step Guide

Machine learning and artificial intelligence have created a new technological landscape and a wealth of emerging opportunities for job seekers. But how do you enter a field as new and competitive as machine learning, which didn’t even exist 10 to 20 years ago?

This position attracts top talent switching from diverse industries like computer science, software development and data science. However, cracking the industry is possible with a top-notch modern CV ready to pass rigorous application tracking systems.

In this article, we break down how to write a good CV as a machine learning engineer with ready-to-use CV templates and industry-relevant examples you can use to compete for in-demand positions.

In this article, we cover:

• How to prepare a machine learning engineer CV in five steps.

• Must-have skills for a machine learning engineer.

• Writing an impactful personal profile for machine learning jobs.

• Inspiration for work history entries and how to present limited experience.

• How to write a machine learning CV with no experience.

What does a machine learning engineer do? 

Machine learning engineers are vital data science team members. Their core responsibilities include researching, designing and building the artificial intelligence involved in machine learning. They also train computers to learn automatically, developing technologies for products such as self-driving cars, news algorithms and large language models like ChatGPT.

If you're interested in combining your expertise in machine learning with the flexibility and comfort of remote work, pursuing a career as a machine learning engineer offers the opportunity to thrive while working from home.

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Machine learning engineer CV example 

In this sample UK machine learning engineer CV, Abbie demonstrates an arsenal of technical abilities combined with extensive practical experience, utilising the Wisconsin CV template for a clear and confident presentation. 

What to include in a machine learning engineer CV? 

Firstly, it is important to know how long your CV should be. Typically, for a machine learning position, this will be no more than two A4 pages. When it comes to crafting your CV, it's essential to tailor your document to meet the requirements of the position you are applying for while including the key components. These include:

• A strong personal profile outlining your experience and aspirations in machine learning.

• Experience and projects such as past roles, internships or engineering bootcamps.

• Technical skills like coding, data management or knowledge of algorithms.

• Education such as a related degree in computer science plus specialised training.

A strategic way to begin the CV writing process is by creating a master CV. This comprehensive version serves as a foundation, allowing you to efficiently customise your application for various industries, maximising your adaptability across the diverse opportunities available in machine learning.

How to write a machine learning engineer CV: 5 steps with examples 

1. What are the important skills for a machine learning engineer to have on a CV? 

Knowing how to put skills on a CV to showcase how you excel as a machine learning engineer is crucial for getting to the first round of interviews and making it through the paper sift. Keep in mind that the skill set of a machine learning engineer, although diverse, is largely technical.

Applicants working as a data analyst, developer or engineer may identify some transferable competencies such as an aptitude for mathematics, coding languages and compiling data sets.

If you are entering the workforce after graduation, focus on leveraging your education, personal projects and practical knowledge from networking or online resources.

Essential skills to become a machine learning engineer:

1. Statistical analysis and mathematical skills: Proficiency in statistics and mathematics is vital to design and implement algorithms that help make data-based predictions.

2. Programming skills: Knowledge of programming languages such as Python or Java is crucial as they are often used in building and implementing models.

3. Data wrangling abilities: The ability to manipulate raw data and convert it into a more usable format is essential, as machine learning heavily depends on data quality and structure.

4. Knowledge of machine learning algorithms: Understanding various machine learning algorithms, from simple linear regression to complex deep learning networks, is necessary to apply the right tool to solve specific problems.

5. System design: Capabilities to design efficient systems that integrate well with existing architectures, ensuring that machine learning models can scale and perform optimally.

How to list soft and technical skills on a machine learning engineer CV

Firstly, distinguish between your core technical skills and those soft skills you believe best characterise your working style such as teamwork, communication or organisation. Integrate your soft skills into the personal profile and work experience sections while creating a separate headed section for technical abilities, labelled ‘Skills’.

2. How to write a personal profile for a machine learning engineer CV

When writing an effective personal profile on a CV, be short and to the point using no more than 70 words. This concise text does not use pronouns and always starts with a powerful opening statement.

Your personal profile should set the tone for the rest of your document. Show your motivations for entering the machine learning field, your level of experience plus the relevant soft skills you feel define your working style.

The following examples blend a strong motivation for working in the machine learning field with technical prowess and sought-after soft skills.

Browse our internship CV example for more inspiration.

Refer to the graduate CV example for further guidance.

If you’re looking for inspiration on how other industries approach this section, read our articles for business analyst, IT and consultant.

3. How to include relevant machine learning engineer work experience 

When outlining your work experience on a CV it is important to keep things clear and concise. Use this space to show you have the collective experience to make a positive difference in the field. For each entry, include a short paragraph detailing core tasks, followed by two bullet points showing quantifiable achievements.

Hiring managers in this young profession know direct work experience is hard to come by and are interested in transferable experiences from other areas and how well you can adapt to the role. Similar to jobs like cyber security or prompt engineer, it is here you should outline relevant private or professional projects and underscore the soft and transferable skills you bring.

Machine learning engineer CV work experience examples

Machine learning engineer | Wey Aye AI, Newcastle | 2021 - Present

Responsible for developing and optimising machine learning models to automate and improve business processes, effectively leveraging data analytics and model training. Engage in collaborative project management and technical documentation, while mentoring junior engineers. Utilise advanced algorithms and data handling techniques, demonstrating strong technical proficiency and communication skills.

• Increased model accuracy by 20% through advanced feature engineering and regularisation techniques.

• Reduced data processing time by 35% by optimising machine learning algorithms and streamlining data ingestion pipelines.

Machine learning engineer intern | BrainBot, Manchester | 2022

Supported the machine learning team by designing and testing algorithms for user engagement platforms, performing data analysis, and enhancing existing machine learning frameworks. Contributed to research and development initiatives, gaining hands-on experience in machine learning applications and collaborative software development environments.

• Helped boost user retention rates by 15% by implementing personalised recommendation systems.

• Assisted in reducing model training costs by 25% by integrating more efficient data preprocessing methods.

Graduate machine learning engineer | See You Data, Birmingham | 2023-Present

Focused on building and deploying predictive models to analyse consumer behaviour, utilising cloud technologies and machine learning libraries. Played a key role in data gathering, preprocessing, and model validation, ensuring the robustness and scalability of solutions within a dynamic team setting.

• Achieved a 10% increase in prediction accuracy by employing ensemble methods and continuous model evaluation.

• Streamlined model deployment processes, achieving a 40% improvement in deployment time on cloud platforms.

Including work experience on a machine learning engineer CV with no practical experience

As a role with a relatively short history, applicants entering the machine learning field often come from other industries or as recent graduates. Consequently, many who apply for machine learning engineer positions have little to no experience.

If this is the case for you, channel your personal projects, volunteer work or internship experiences to maximum effect. If you’re entering the field after a career change, try to adapt previous experiences and highlight relevant transferable skills. For example:

Data analyst | Big Ship Analytics, Bristol | 2019-2023

Transitioning from a Data Analyst role, leveraged strong analytical skills and experience in statistical software to dive into machine learning. Led data-centric projects that align closely with machine learning objectives, such as predictive analytics and pattern recognition. Developed proficiency in Python through personal projects, and completed an online machine learning course to enhance technical capabilities.

• Enhanced business decision-making by developing a predictive model that improved forecasting accuracy by 30%.

• Volunteered in a community project to develop a machine learning model for local traffic pattern prediction, enhancing traffic management efficiency by 20%.

4. How to include education on a machine learning engineer CV

When adding an education section to a CV, it's best to list your qualifications in reverse chronological order, starting with the most recent degree. Include the degree name, institution and graduation year. If space allows, highlight relevant coursework, projects and any academic honours to showcase your background and preparation for a career in machine learning.

If you are a student or undergraduate, employers typically look for a minimum of a bachelor's degree in Computer Science, Mathematics and Statistics or a related field. As the field of machine learning is relatively new and rapidly evolving, dedicated machine learning degrees are rare, but some institutions offer specialised courses within broader degree programs.

How to format university degrees on a CV

• Name of degree

• Name of university

• Dates of course or (expected) completion date

• Location.

MSc Computer Science, University of Newcastle, 2024

BSc Hons in Mathematics, University of Aston, Birmingham, 2019

5. Include additional information to add value to your CV

Competition for machine learning engineer positions is fierce. Set yourself apart by showing additional sections such as courses and certificates, hobbies and interests or other notable achievements. Remember to keep each relevant to the job description and employer.

Courses and Certificates

AWS Certified Machine Learning - Specialty, AWS, 2024

Neural Deep Learning Specialisation, DeepLearning.AI, UK, 2023

Hobbies and Interests

Competitive coding, mathematical problem solving and robotics

How to write a machine learning engineer CV with little to no experience 

Machine learning is a field wide open to applicants from various professional backgrounds. Below are a few points to keep in mind when creating a machine learning CV with little to no experience.

1. Create a personal profile showing enthusiasm for AI and machine learning

Begin your CV with a compelling statement that reflects your passion for machine learning and AI. Highlight your core soft skills, ambitions, relevant achievements, personal projects or continuous learning efforts.

2. Focus your work experience on transferable skills and project contributions

Even without direct experience, detail any previous roles or projects where you've utilised analytical, programming or problem-solving skills. Discuss contributions to team projects or any tasks that involved data handling, software tools or technology that align with machine learning principles.

3. Highlight technical and soft skills

Separate your skills into Technical and Soft Skills. For technical skills, list programming languages (Python, R), software (MATLAB), or platforms (TensorFlow) you're familiar with. For soft skills, emphasise critical thinking, perseverance, and eagerness to learn, which are crucial for a career in machine learning.

4. Emphasise relevant educational coursework and projects

Include your degree(s) and any relevant courses like statistics, computer science or data analytics. Focus on academic projects or group work that involved machine learning concepts, even if they were part of a wider module or track.

Key takeaways 

Our five key takeaways for crafting a first-class machine learning engineer CV in the UK:

1. Create a strong personal profile: Start with a powerful statement showcasing your enthusiasm for AI and machine learning. Highlight any relevant projects, courses, or personal interest in the field to demonstrate your commitment and knowledge base.

2. Highlight transferable skills in work experience: Use your previous roles to showcase applicable skills such as data analysis, coding, or problem-solving. Detail any projects or tasks that align with machine learning competencies.

3. Emphasise technical and soft skills: Separate your technical skills (like programming languages and machine learning tools) and soft skills (such as critical thinking and teamwork) on your CV. This demonstrates a well-rounded skill set.

4. Focus on relevant education and continuous learning: List your educational background in reverse chronological order, emphasising any coursework or projects related to machine learning or data science. Include any ongoing learning like online courses or certifications.

5. Include personal projects and volunteering: If applicable, add personal projects or volunteer work that involves machine learning or data analysis to show practical experience and initiative in this area.

Next steps?

Iron out any creases using our intuitive CV maker with 20+ CV templates and professional designs to choose from. To accompany your CV, discover our cover letter templates. If you don’t want to leave anything to chance, connect with our professional CV Writing Service. Draw inspiration from our blog for tips on how to track your job applications and ultimately best practices for sending your CV via email.

FAQs 

Can I get a job by learning machine learning?

Yes, learning machine learning can lead to job opportunities, especially as the field grows and evolves. Employers value candidates with skills in data analysis, programming and the ability to build and deploy machine learning models.

How much do machine learning engineers make in the UK?

Machine learning engineers in the UK typically earn between £40,000 and £80,000 annually, depending on experience, location and the specific industry they work in. Though it's not one of the highest paying jobs in the UK, there is potential for this type of job to earn above the national average.

How do I land my first job as a machine learning engineer?

To land your first job as a machine learning engineer, focus on building a strong foundation in relevant skills through education, personal projects and internships. Networking and showcasing your technical capabilities through a well-crafted CV and portfolio can also be crucial.

Are machine learning engineers in demand in the UK?

Yes, machine learning engineers are in high demand in the UK, driven by the increasing integration of AI technologies across various sectors such as finance, healthcare and technology. If you're passionate about leveraging cutting-edge technology to innovate and improve workflows while also having a keen interest in enhancing workplace efficiency, then the role of a machine learning engineer might be the perfect fit for you.

Do machine learning engineers have a future?

The role of machine learning engineers has a promising future, with ongoing advancements in AI and increasing reliance on data-driven decision-making in businesses creating more opportunities in the field.