What you need to know about a machine learning engineer job

What is a machine learning engineer?

A machine learning engineer is responsible for designing and building systems that learn from data, improve over time, and are able to predict or automate decision-making processes. 

They do this by working with large data sets and developing algorithms and models through programming and software development. 

Responsibilities of a machine learning engineer 

Machine learning engineers are in demand across a number of sectors, including security, aerospace and defence, transportation and water. At AtkinsRéalis , these professionals play a vital role in helping us solve problems in the built environment, both efficiently and effectively. 

You’ll need a solid understanding of mathematics, statistics, and data science in this role, to build machine learning models. It requires you to combine technical knowledge with soft skills such as interpersonal skills, problem-solving, and attention to detail.

Here’s what to expect as a machine learning engineer: 

• Analyzing data - you’ll collect and analyze large amounts of data from various sources to build and train machine learning models.
• Developing algorithms - solve specific problems or automate processes by building algorithms.
• Testing models - based on data analysis, you’ll ensure that the output from these models is accurate and reliable. 
• Collaborating with teams - working closely with data scientists and software developers to ensure that the models you’ve built integrate with existing systems.
• Monitoring models - responsible for monitoring the performance of deployed models and building out improvements where necessary. 

Why is this field important? 

With approximately 2.5 quintillion bytes of data being created each day, it is becoming increasingly important to be able to easily analyze large and complex data sets. Machine learning automates this process giving organizations across the world the gift of agility. 

This level of automation increases efficiency and saves a lot of time, hence reducing costs. In fact, 73% of IT leaders credit automation for helping employees save 10-50% of the time they previously spent on manual tasks. 

Machine learning facilitates innovation through predictive analytics and its ability to make data-driven decisions. For example, in transportation, machine learning models are used to analyze traffic patterns to optimize routing and scheduling for delivery trucks. Or in banking, these models are able to flag fraudulent behaviours. 

Unlock new opportunities 

A McKinsey survey found that 76% of organizations say they prioritize machine learning over other IT initiatives, and 64% say the priority of machine learning has increased relative to other IT initiatives. 

AI and machine learning are being adopted across the world in a variety of different industries. This means that the scope for machine learning engineers is wide. 

You’ll have your pick of the types of organizations you work with from startups to large corporations or government agencies. Not only that, you’ll have the opportunity to work across industries such as finance, healthcare, industrial and manufacturing, cities and development and more. 

Take your machine learning career to Canada 

If harnessing the power of data and automation excites you, a career as a machine learning engineer could be right for you. We are looking for people who are passionate about identifying unique drivers of change to deliver outstanding outcomes for our clients. 

Engineer a better future for our planet and its people with AtkinsRéalis as a machine learning engineer. Join our talent community or sign up for job alerts.