What are the Deep Learning Job Roles and Responsibilities?

The most in-demand deep learning roles are deep learning engineer, machine learning engineer, data scientist, AI research scientist, computer vision engineer, and natural language processing engineer. Deep learning professionals are mainly responsible for designing and developing deep learning models, data preparation and model evaluation, deployment and continuous improvement, etc. 

If you are starting to build a career in deep learning, you must know about the in-demand job roles and responsibilities of a deep learning engineer. This blog helps you attain detailed and valuable insights into the topic of deep learning job roles and responsibilities. 

Key Roles and Responsibilities of a Deep Learning Professional

Here are the key deep learning job roles. 

Let us explore the detailed responsibilities of the deep learning job roles. 

1. Deep Learning Engineer

Deep Learning Engineers are the one who designs and develops neural networks. The neural networks developed by deep learning engineers enable the machines to learn from complex data. The seamless functioning of AI-powered real-world applications, such as image or speech recognition, is performed easily by optimising deep learning systems by expert deep learning engineers. 

Key Responsibilities of a Deep Learning Engineer

Deep learning engineers are responsible for performing tasks such as:

Examine: What is Deep Learning and How Does It Work?

2. Machine Learning Engineer

Machine learning engineers are responsible for building scalable machine learning systems. These machine learning models are capable of powering real-world applications. To deploy high-performing models, machine learning engineers make use of expertise in deep learning and data science.  

Taking a professional training in machine learning can help you efficiently execute the responsibilities of a machine learning engineer. 

Key Responsibilities of a Machine Learning Engineer

Machine learning engineers are responsible for tasks including,

Explore the Best Languages For Machine Learning, to upskill and build performance-driven AI models. 

3. Data Scientist

Data scientists are responsible for extracting insights from complex data by applying advanced analytics and neural network expertise.  As a data scientist, you must be an expert in deep learning for the effective performance of tasks. The data scientists are the ones who make predictions, find business solutions and strategies, and support data-driven strategies. 

Key Responsibilities of a Data Scientist

Data scientists are mainly responsible for the following tasks.

Checkout, Data Science vs Machine Learning: What's the Difference? To know more about the respective job roles. 

Here is the Complete Guide to Data Science Career Path.

4. AI Research Scientist

AI research scientists perform experiments and research to advance deep learning techniques. As an AI research scientist, you perform tasks like researching and working on new algorithms, model architectures, and approaches to develop artificial intelligence for better performance.

Key Responsibilities of an AI Research Scientist

AI research scientists are responsible for several highly significant tasks, such as:

Here is a guide on How to Build a Career in Artificial Intelligence. 

5. Computer Vision Engineer

The computer vision engineers specialise in deep learning models that interpret visualised data. This is a specialised branch of AI that offers rewarding opportunities. As a computer vision engineer, you have to work on applications that include performance like object detection, facial recognition, and visual inspection systems by enabling machines to interpret data from images and videos. 

Key Responsibilities of a Computer Vision Engineer

The computer vision engineers are responsible for tasks such as

6. Natural Language Processing Engineer

Natural language processing  (NLP) engineers are responsible for developing deep learning models that understand and generate human language. As an NLP engineer, you have to work to optimise the performance of applications such as chatbots, sentiment analysis, language translation, and text summarisation. 

Key Responsibilities of a Natural Language Processing Engineer

The natural language processing engineers are responsible for

Why Deep Learning Skills Are in Demand

Artificial intelligence is leaping towards great advancements. In such a context, deep learning skills have the highest demand across the industries worldwide. If you intend to build a career in deep learning, it is necessary to build deep learning skills with the help of professional training in deep learning. Have you ever wondered what the reason is for the rising demand for deep learning skills? Here we have listed some relevant reasons below. 

Conclusion

Deep learning skills have relevance across professions in engineering, research, and applied analytics. For someone who is aspiring to become a deep learning professional, understanding the major job roles and responsibilities is important. Right guidance helps aspiring professionals to choose the right educational path in AI that is ideal for them.