Machine Learning Engineer

Machine learning engineers build the AI that powers the future, turning data into intelligent systems that automate, predict, and innovate across industries. Learn more about the skills and training you need to become a machine learning engineer.

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Machine Learning Engineer

Role profile

What does a machine learning engineer do?

Machine learning engineers build and optimise ML and AI systems that learn from data to make predictions and automate tasks. They design algorithms, train models, and deploy them into real-world applications like recommendation engines, fraud detection, and self-driving cars.

Combining software engineering with data science, they ensure AI models are efficient, scalable, and continuously improving. Their work powers innovations that shape the future of technology.

Why do businesses need machine learning engineers?

Machine learning engineers play a crucial role in businesses by developing AI systems that drive automation, efficiency, and innovation.

They build and deploy models for tasks like customer personalisation, fraud detection, and process optimisation. Working closely with data scientists and engineers, they ensure AI solutions are scalable and effective.

Their expertise helps businesses harness the power of AI, making data-driven decisions and staying competitive in a rapidly evolving market.

What kind of projects might I work on as an ML Engineer?

Machine learning engineers are in demand across many industries right now, with organisations needing to develop their automation capabilities. Here are some of the key projects they could work on: 

ML engineers in Retail:

- Building recommendation algorithms that analyse customer behavior to suggest personalised products.
- Training demand forecasting models to predict sales trends and optimise inventory levels.
- Developing computer vision systems for automated checkout, shelf monitoring, and theft detection in stores.

ML engineers in Finance:

- Designing fraud detection models that learn patterns of fraudulent activity and flag suspicious transactions in real time.
- Building AI-driven risk assessment models to evaluate loan applicants and investment opportunities.
- Optimising algorithmic trading systems by training models to analyze market trends and execute trades efficiently.

ML engineers in Healthcare:

- Training deep learning models to detect diseases from medical scans like X-rays and MRIs.
- Building predictive models that analyse patient data to anticipate deterioration and recommend interventions.
- Developing NLP algorithms to extract insights from medical records and assist in diagnosis.

ML engineers in Environmentalism:

- Developing machine learning models that analyse weather and satellite data to predict wildfires and hurricanes.
- Optimising smart grid energy distribution by training models to forecast demand and adjust power supply.
- Using computer vision models to analyse satellite imagery and detect deforestation or climate changes.
Why it matters

ML engineer insights

£60k

Average UK salary

74%

Yearly increase in job postings

Top 10

Job role growth between 2023 and 2027

Training and courses

How to become a machine learning engineer

Machine learning engineer training

Explore the training and certifications available to help you on your journey to becoming a machine learning engineer.

If you're a business looking to upskill your team, or hire an apprentice, get in touch with our team to discuss your requirements. 

Learn machine learning online

Machine learning online library

Discover unlimited learning with a subscription to our online learning platform, including hours of machine learning courses, hands-on labs and exams. 

Machine learning courses

Explore our range of machine learning courses, delivered by industry-experts. 

Develop programming skills

Python

Deepen your understanding of data science by developing your skills in Python, enabling you to produce valuable business insights using sophisticated statistical models.

R

Develop the skills and techniques you need to write powerful programs to analyse and visualise your data with our R modelling language courses.

Explore data, AI and ML apprenticeships

Data apprenticeships

Learn more about how to upskill your team with AI and Data apprenticeship programmmes, including the Data Analyst L4 and Data and AI Specialist Level 7. 
What our experts say

Insights from the experts

“We're entering a future where 80% of our work may be performed by AI. How do we deploy technology capable of learning the most complex cognitive tasks?

“The answer is simple. We develop soft and hard skills needed to work in a hybrid world. Organisations are creating data and AI-driven cultures. They are learning the tools and techniques to successfully utilise AI to reduce toil and increase impact, safely, and effectively. We need to prepare AI skills now, to ensure maximum positive impact for years to come.”

Vicky Crockett , Portfolio Director - AI

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