How to Be Cognitive Computing Engineer - Job Description, Skills, and Interview Questions

Jul 2, 2020 / 5 Minutes Read / By Albert

How to Become

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Cognitive Computing is a rapidly growing field of technology that is transforming the way computers and machines are used to understand and interact with humans. By combining artificial intelligence, natural language processing, and machine learning, cognitive computing systems can simulate human thought processes to provide valuable insights and predictions. This is allowing organizations to make faster, more accurate decisions and improve customer experience.

As a result, the demand for Cognitive Computing Engineers is increasing rapidly. Companies are seeking engineers with a deep understanding of programming languages and data analysis, as well as expertise in machine learning and artificial intelligence to help them stay ahead of the competition. With the right knowledge and experience, Cognitive Computing Engineers can help businesses make better decisions, increase efficiency, and gain a competitive edge.

Steps How to Become

Obtain a Bachelor's Degree. A bachelor's degree in computer science, software engineering, mathematics, or a related field is required to become a cognitive computing engineer. You should also have experience with programming languages such as Java, C++, or Python.
Develop Cognitive Computing Skills. Cognitive computing engineers need to understand the principles of machine learning and artificial intelligence, as well as have strong analytical and problem-solving skills. You should also be familiar with natural language processing (NLP) and be able to implement algorithms and design software applications that can process large amounts of data.
Gain Professional Experience. Gaining professional experience is essential to becoming a cognitive computing engineer. You should look for internships or entry-level positions at tech companies where you can work on developing cognitive computing applications and gain hands-on experience.
Consider Certification. Consider obtaining industry certifications in areas such as artificial intelligence, natural language processing, or machine learning. This can demonstrate your expertise and help you stand out to potential employers.
Stay Up-to-Date on Developments. The field of cognitive computing is constantly evolving, so its important to stay up-to-date on the latest developments and trends in the industry. You should also keep your skills up-to-date by taking courses or attending conferences and seminars.

Cognitive computing engineering is a specialized field of computer science that involves developing and using systems that can reason, learn, and interact with humans in order to solve complex problems. To be an ideal and qualified cognitive computing engineer, one must possess a combination of technical, scientific, and creative skills. A strong technical background in computer programming and mathematics is essential, as is an aptitude for problem solving.

Understanding of artificial intelligence principles, algorithms, and data structures, as well as experience working with large datasets, are all beneficial. creative thinking, an ability to think outside the box, and excellent communication skills are needed to effectively design and develop cognitive computing solutions. All of these skills combined can help create an ideal and qualified cognitive computing engineer.

You may want to check Cognitive Data Analyst, Cognitive Architect, and Cognitive Behavioral Health Nurse for alternative.

Job Description

Design and develop cognitive computing algorithms that enable the development of machine learning and artificial intelligence applications.
Develop, modify and maintain software applications to support cognitive computing.
Analyze and understand data from various sources to build cognitive computing models.
Develop and implement test plans to ensure accuracy of models.
Research and evaluate emerging technologies in the field of cognitive computing and recommend changes or upgrades to existing systems.
Collaborate with other engineers, scientists and data scientists to refine and improve cognitive computing models.
Develop detailed documentation of cognitive computing algorithms and models.
Design user interfaces for cognitive computing applications.
Troubleshoot and debug cognitive computing applications when necessary.
Develop training materials for end users on how to use cognitive computing applications.

Skills and Competencies to Have

Artificial Intelligence (AI)
Machine Learning (ML)
Natural Language Processing (NLP)
Knowledge Representation and Reasoning (KRR)
Computer Vision (CV)
Data Mining and Data Analytics
Probability and Statistics
Algorithm Design and Analysis
Software Engineering
Cloud Computing
Database Design and Management
Big Data Management
Robotics
Human-Computer Interaction (HCI)
Computer Security
Networking Protocols
System Architecture Design

Cognitive Computing Engineers are responsible for the development, implementation, and maintenance of cognitive computing systems. As such, the most important skill for a Cognitive Computing Engineer to possess is an ability to understand complex algorithms and technologies. In order to do this effectively, one must have a strong understanding of data structures, machine learning, natural language processing and computer vision.

Cognitive Computing Engineers must be familiar with programming languages such as Python and Java. Furthermore, they should be comfortable working with large datasets and have experience working with cloud-based technologies. Being able to work collaboratively with other teams and possessing excellent problem-solving skills are also essential for success in this role.

Having a background in mathematics or statistics can also be of great help in this field. Finally, having a good understanding of ethical considerations around using data can go a long way in helping Cognitive Computing Engineers make responsible decisions.

Cognitive Behavioral Health Associate, Cognitive Behavioral Health Clinical Supervisor, and Cognitive AI Engineer are related jobs you may like.

Frequent Interview Questions

What experience do you have in cognitive computing engineering?
How do you stay current with the latest advancements in cognitive computing engineering?
What challenges have you faced in your previous experiences with cognitive computing engineering?
What strategies do you use for developing and deploying cognitive computing systems?
How do you maximize the accuracy and performance of cognitive computing models?
What methods do you use to ensure the ethical use of data in cognitive computing systems?
Describe a project you have led in cognitive computing engineering.
How do you diagnose and troubleshoot problems in cognitive computing systems?
How do you evaluate and improve the accuracy of a cognitive computing system?
What techniques do you use for optimizing cognitive computing algorithms?

Common Tools in Industry

Natural Language Processing (NLP). A branch of artificial intelligence that deals with the understanding and analysis of human language, enabling machines to read and understand human language. (e. g. Googles Smart Reply)
Machine Learning. A field of computer science that uses algorithms to learn from data, allowing machines to improve their performance without explicit programming. (e. g. IBM Watsons AI-driven medical diagnostics)
Deep Learning. A subset of machine learning involving artificial neural networks that use multiple layers of non-linear processing for feature extraction and pattern recognition. (e. g. Googles Deep Dream)
Automated Reasoning. The process of using computers to draw logical conclusions from input data. (e. g. Googles AlphaGo AI)
Natural Language Generation (NLG). A branch of artificial intelligence that focuses on automatically generating human-readable text from structured data. (e. g. Apples Siri)
Knowledge Engineering. The process of constructing and maintaining knowledge-based systems by hand or with automated tools. (e. g. Amazons Lex chatbot)

Professional Organizations to Know

Association for Computing Machinery (ACM)
Institute of Electrical and Electronics Engineers (IEEE)
International Association for Computational Linguistics (IACL)
International Neural Network Society (INNS)
International Society for Computational Intelligence (ISCI)
International Society for Artificial Life (ISAL)
International Society for Optical Engineering (SPIE)
Machine Learning for the Artificial Intelligence (MLAI)
North American Fuzzy Information Processing Society (NAFIPS)
Robotics: Science and Systems (RSS)

We also have Cognitive Neuroscience Professor, Cognitive Neuroscience Associate Professor, and Cognitive Developmental Psychologist jobs reports.

Common Important Terms

Machine Learning. A type of artificial intelligence that provides computer systems the capability to learn and adapt using algorithms that can identify patterns in data.
Natural Language Processing (NLP). A type of artificial intelligence that allows computers to interpret and understand human language.
Deep Learning. A type of machine learning that uses layers of neurons to process data, similar to the way a human brain would.
Knowledge Representation. A way of representing knowledge in a computer, such as through rules, frames, ontologies, or semantic networks.
Text Mining. The process of extracting information from unstructured text data, such as from emails, documents, web sources, etc.
Ontologies. A formal representation of knowledge about a domain, which can be used for reasoning and inference.
Cognitive Modeling. A field of artificial intelligence that studies how an intelligent system can use acquired knowledge and experience to make decisions or solve problems.
Cognitive Computing. A type of artificial intelligence that combines machine learning, natural language processing, deep learning, knowledge representation, text mining, ontologies and cognitive modeling to build systems which are able to think like a human.

Frequently Asked Questions

What is a Cognitive Computing Engineer?

A Cognitive Computing Engineer is a specialist in the field of Artificial Intelligence (AI) and Machine Learning (ML) who applies these technologies to solve complex problems.

What skills are necessary for a Cognitive Computing Engineer?

Cognitive Computing Engineers must have excellent knowledge of programming languages such as Python, Java, and C++; expertise in AI and ML algorithms; familiarity with deep learning frameworks such as TensorFlow and Keras; and experience in data analysis, modeling, and optimization.

What is the job outlook for a Cognitive Computing Engineer?

According to the U.S. Bureau of Labor Statistics, the number of Artificial Intelligence and Machine Learning jobs is expected to increase by 28% from 2019-2029.

What types of companies hire Cognitive Computing Engineers?

Companies in a variety of industries, including healthcare, finance, technology, and retail, are increasingly looking to hire Cognitive Computing Engineers to help them create more efficient and effective AI-driven solutions.

What is the typical salary for a Cognitive Computing Engineer?

The average salary for a Cognitive Computing Engineer is $111,530 per year according to Glassdoor.

Web Resources

Home | Cognitive Computing Laboratory | West Virginia University cognitivecomputinglab.faculty.wvu.edu
Cognitive engineering: The brain behind innovative work systems news.engineering.iastate.edu
Cognitive Science | Cognitive Science Program | UNC Charlotte cogsci.charlotte.edu