The role of a Machine Learning (ML) Engineer can be difficult to describe in simple term. Let’s try! Firstly, maching learning is a form of artificial intelligence, it makes predictions using data.
When you hire someone to be a ML Engineer they will be primarily focused on the researching, building and designing self-running artificial intelligence (AI) systems to automate predictive models.
The list of skills and experience required to be a ML Engineer is quite extensive:
- Strong degree in statistics, mathematics, computer science
- Experience in data science
- Software engineering
- Coding in program languages including Python, Java, C, C++, R, Javascript
- Experience across ML frameworks, libraries and packages
- The ability to understand data structures, data modelling and software architecture
The responsibilities of a ML Engineer within an organisation can vary, but can include:
- Designing ML systems
- Researching and implementing ML algorithms and tools
- Selecting data sets and verifying data quality
- Transforming and converting data science protyles
- Statistical analysis
- Running machine learning tests
- Using results to improve models
Many professionals that go into ML do it because it provides them with the opportunity to utilise their mathematical skills, and they enjoy finding practical applications for complex equations and theories.
