5 More Types of Software Development

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Based on the success of our previous article on 10 types of software development , we’ve decided to build on that to share 5 more types of what you could be doing as a software engineer in the field!


1. Front-end web development

First impressions matter, and that’s why front-end web developers matter. Billions of websites each try to get your attention each day, and front-end developers use code and frameworks to make sure your experience using a website is a great one.

                                                                                           Web development technologies


        Front-end development is increasingly becoming cross platform – mobile, tablet, and desktop 

This includes everything from images, layout, colour schemes, and placing things where they are easy to find. Front-end development requires not just software engineering skills, but a flair for design and an eye for detail – making this one of the most in-demand roles.

Popular technologies: Javascript, Javascript libraries such as JQuery/D3, Python, Django, CSS/HTML



2. Product Management

As software and tech products get more complex, the role of Product Manager is becoming more popular. Made famous by the Associate Product Manager programme, launched by Google – the product manager role was intended to fill a specific niche. Google needed fresh minds to help build their revolutionary products, so they invented a job just for it. The first Product Manager, Brian Rakowski (https://www.linkedin.com/in/brian-rakowski-45a4832b), went on to create Gmail – so it’s obvious why the Product Manager position has now been adopted by nearly every tech company under the sun, including Facebook, Uber, and Microsoft. 

        PMs are at the intersection of user needs, technology, and business

Product Managers have technical software engineering ability and experience, but rather play a role interfacing between software teams and users. PMs are constantly thinking about how the user experiences an app, tech product, or website and are always trying to improve the overall experience for a user.

Popular technologies: A pen and paper, email, and Google Slides!



3. Site Reliability Engineer

As software becomes more and more critical in our lives, making sure it’s always working is key. Imagine you’re binge-watching the new House of Cards on Netflix, and Netflix goes down. Site Reliability Engineers are there to make sure that doesn’t happen.

While a stressful role, the job is incredibly rewarding. As a SRE, you may be constantly ‘on call’ for any errors or outages of a service, and will be timed to get it fixed as soon as possible. You’ll be paid top dollar for that commitment though and recognised for your insane ability to fix problems fast.

Popular technologies: Python, Java, debugging tools

4. Machine Learning Developer

A more specific role within Data Science, Machine Learning developers are becoming more popular as more and more data becomes available. Platforms rich in data, such as Google or Facebook, have some of the strongest teams of machine learning developers who use that data to deploy algorithms that slightly improve your experience as a user. 

        Data science encompasses machine learning, and many other disciplines

For example, every time Facebook recommends a friend for you to connect with – it isn’t random, but rather the result of a complex machine learning algorithm that has learnt the people you are likely to know and interact with. Machine Learning developers design this algorithm, and as more tech companies compete neck-on-neck for your attention, there’s only going to be more demand for the skillset.

Popular technologies: Python, R, Python packages such as Sci-kit learn.



5. Natural Language Processing developer

Another role falling under Data Science, Natural Language Processing developers specialise in understanding data in the form of languages – that may be books, web pages, social media posts.


        Machine translation systems – such as Google translate – as a popular application of NLP

They use this data to deliver a better technical experience. For example, ever wondered how the Gmail Spam filter works? Natural Language Processing techniques are used to automatically determine from the content of an email whether it is likely to be spam, and then hide it from you. Other NLP products include Google Translate – entirely built using algorithms written using phrase-based machine translation techniques.

Popular technologies: Python, Python packages such as NLTK, parsers, web crawlers.


Interested in learning more about Machine Learning and Natural Language Processing? Check out Hyperion’s Certified Data Scientist MicroDegree, where you’ll build your own spam filter in Python!