A deep learning engineer is in charge of researching, building and maintaining algorithms that power Artificial Intelligence and Machine Learning systems and applications. These professionals act as crucial members of the data science team and are usually involved in the work of various technologies including data science and Big Data. What does a deep learning engineer do?
What is Deep Learning?
Deep learning is a part of Machine Learning (ML) and is a technique that deals with algorithms that teaches computers to learn by example.
Human beings are able to learn information thanks to the millions of neurons that are interconnected in our minds. Computers, on the other hand, have neural networks that are made from multiple layers of software nodes. These networks are in charge of simulating the way a human brain works, allowing computers to learn from copious amounts of data.
Deep learning drives numerous AI applications, thereby improving automation and performance. A few examples of deep learning include:
- Virtual assistants
- Face recognition
- Personalised shopping, etc.
Deep learning vs machine learning: The difference
Both machine learning and deep learning are algorithms that use data to learn. However, there is a key difference in how each processes said data and learns from it.
Machine learning is the term generally used to describe the process of a computer learning from data. Data is fed into an algorithm and then used to train a model. These models then progressively get better at performing specific functions as they take in new data – the more data the machine parses, the better it can become at performing a task.
Machine learning does require human intervention if the algorithm returns an inaccurate or wrong prediction.
Deep learning, on the other hand, improves its outcomes through repetition, without human intervention. It does this by using a layered structure of algorithms called an artificial neural network (ANN).
While a machine learning algorithm can learn from relatively small sets of data, a deep learning algorithm requires big sets of data which can include diverse and unstructured data.
Keep in mind that while deep learning is a subset of machine learning, both of them are in turn subsets of Artificial Intelligence.
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Responsibilities of a Deep Learning Engineer
Deep learning engineers are in charge of building and maintaining algorithms that power Artificial Intelligence applications. They also carry out tasks like defining data requirements for a project as well as collecting, labelling, inspecting, and cleaning data.
These engineers maintain existing AI systems by adding new features or fixing bugs as necessary and also define evaluation metrics and searching hyperparameters.
Deep learning engineers develop custom neural network architectures for specific needs and convert prototyped code into production code.
What are the responsibilities of a deep learning engineer?
- Build and maintain algorithms that power AI applications
- Define data requirements for a project
- Collect, label, inspect and clean data
- Maintain existing AI systems by adding new features
- Fixing AI bugs
- Define evaluation metrics
- Define searching hyperparameters
- Develop custom neural network architectures for specific needs
- Convert prototyped code into production code
- Set up cloud environment to deploy model
- Improve response times
Skills of a Deep Learning Engineer
A deep learning engineer has strong mathematical and programming abilities as well as extensive data engineering knowledge. They also have experience with applications of statistical modelling and inference as well as an understanding of deep learning algorithms and frameworks.
Engineers in this field are familiar with common neural network architectures like Autoencoders, Deep Belief Networks (DBNs), Convolutional neural networks (CNNs), etc.
They also have knowledge of speech recognition, natural language processing (NLP), and computer vision.
In terms of soft skills, deep learning engineers have strong analytical thinking, collaboration, communication and problem-solving skills.
What are the skills of a deep learning engineer?
- Strong mathematical abilities
- Knowledge of OOP languages such as Python, Java, and C++
- Extensive data engineering knowledge
- Experience with applications of statistical modelling and inference
- Understanding of deep learning algorithms and frameworks
- Familiarity with common neural network architectures like Autoencoders and DBNs
- Knowledge of speech recognition
- Experience with UI technology like Django and Flask
- Knowledge of natural language processing (NLP)
- Familiarity with computer vision.
- Experience with workflow management tools like Git for version control
- Familiarity with cloud technologies such as AWS and Azure
- Strong analytical thinking
- Good collaboration skills
- Good communication skills
- Strong problem-solving skills
How to become a Deep Learning Engineer
To work as a deep learning engineer, you will need to have a Bachelor’s in Computer Science, Statistics, Mathematics, or a related field.
A postgraduate certification in the same fields can also help you in obtaining better jobs as well as specialised courses. See options for a few of these down below:
- Deep Learning Specialization
- Python for Deep Learning: Build Neural Networks in Python
- Complete Guide to TensorFlow for Deep Learning with Python
- Unsupervised Deep Learning in Python
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Deep Learning Engineer Salary
A deep learning engineer can make around $164,300 per year on average in the US. Beginners can expect a salary of around $93,300 per year whereas those with years of experience can expect a salary of around $289,300 per year.
In Germany, engineers in this field can expect a salary in between €69,000 – €123,000 whereas in the UK, they can expect a salary in between £46,000 – £105,000.
How much do deep learning engineers make?
|US||$93,300 – $289,300|
|Germany||€69,000 – €123,000|
|UK||£46,000 – £105,000|
How much do freelance deep learning engineers make?
Deep Learning Engineers on freelancermap charge on average:
Rates in the Deep Learning Industry range between $40 and $96/hour for most freelancers.
The daily rate for Deep Learning Engineers (8 working hours) would be around:
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