ARTIFICIAL INTELLIGENCE ENGINEER SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Aug 1, 2024 - The Artificial Intelligence Engineer possesses a unique blend of creative problem-solving abilities and articulate communication skills, essential for transforming innovative concepts into real-world applications. With a strong foundation in machine learning, this role involves the entire data lifecycle from acquisition and preprocessing to model training and deployment in production environments. Expertise in test automation, coupled with a profound understanding of software testing and automation methodologies, enables the development and architecture of sophisticated automated testing solutions using languages like Java, Python, and Ruby.
Summary of Artificial Intelligence Engineer Knowledge and Qualifications on Resume
1. BS in Computer Science with 2 years of Experience
- Must possess a Final U.S. SECRET security clearance
- Familiarity with the Agile Software Design Life Cycle
- Familiarity with Department of Navy (DON) command organization and IT infrastructure
- Excellent ability to work by deadlines
- Fluent English and Italian, spoken and written
- Distinctive propensity to team working and is at ease mediating even between different requests.
- Open minded to different cultures in working, he always uses a collaborative approach, helping to find shared solutions out of the box.
- Good grasp of technology, passionate about it and informed about evolutions and trends.
- Familiar with and can apply measurement theory, statistics, informatics and physics.
- Previous working experience in Space Business
2. BS in Computer Engineering with 3 years of Experience
- Experience developing large scale, highly available distributed systems
- Strong knowledge of application/component design
- Solid understanding of Pythonic conventions, Object Oriented and Functional programming paradigms
- Solid knowledge of software testing principles
- Experience with Infrastructure-as-code, API design
- Experience with continuous deployment and integration
- Interest or experience with Natural Language Frameworks (e.g., Rasa, Spacy, NLTK), Machine Learning, Automatic Speech Recognition, Text-to-Speech
- Strong verbal and written communication, creative and dynamic thinker
- Ability to articulate and advocate ideas, approaches, or changes in process
- Strong sense of ownership, high attention to detail and quality
- Passion for continuous learning and growth
3. BS in Data Science with 2 years of Experience
- Ability to think independently and innovatively
- Excellent public speaking and personal interaction skills
- Hands-on experience working on enterprise IoT and connected products
- Expert in machine learning to help us extract value from the data.
- Work on all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production
- Hands-on experience working on Test automation software
- In-depth knowledge of software test and automation methodologies
- Able to perform complex test automation investigations, reporting on problems encountered and documenting results for follow-up
- Architect automated testing solutions at the project level and for multiple groups
- Experience in the development of test automation solutions using Java, Python and Ruby
4. BA in Cognitive Science with 3 years of Experience
- Experience in testing firmware and embedded systems.
- Self-motivated individual with the ability to work under minimal supervision
- Solid understanding of the Software Development Life Cycle including Agile methodology
- Experience within and Jenkins, CI/CD and DevOps.
- Experience using the test, test, Unit test frameworks
- Familiar with working with any embedded or telecom or hardware product is desirable
- Ability to work in a fast-paced environment, experience with IoT-based systems
- Experience with multiple AI techniques: Heuristic Search/Planning, Knowledge Representation, Diagnosis, Machine Learning, Cognitive Systems
- Experience in reading scientific papers and replicating methods
- Familiarity with modern software tools and practices
- Self-starting: Can work independently within a multi-disciplinary team
5. BS in Software Engineering with 4 years of Experience
- Familiar with the role of advisory consulting or internal audit processes.
- Experience and confidence in presenting analysis reports and recommendations.
- Possess a good working knowledge of both unstructured (big data) and structured (SQL and RDBMS) data management technologies.
- Experience in cyber security analytics and artificial intelligence.
- Experience with artificial intelligence and machine learning requirements analysis, design, implementation and deployment.
- Experience in SOC of Cloud cyber security services environments.
- Threat intelligence and analysis experience.
- Network security testing experience.
- Experience with high-level programming and data manipulation such as Python, Java, Perl and R.
- Experience performing statistical analysis with tools and libraries such as NumPy, TensorFlow, SciPy and Pandas.
- Experience with unstructured data platforms (“Big Data”), data warehousing and analytics technologies such as Azure Data Bricks and Synapse.
- Experience with one or more of the following technologies: Watson, Google Analytics, McLaren, Splunk, Dark Trace AI, Crowdstrike Falcon or Sapien.
Professional Skills FAQs
What are professional skills?
Professional skills are abilities that help individuals perform tasks effectively in a workplace environment. These skills include both technical competencies required for specific roles and soft skills such as communication, teamwork, and problem solving.
What is the difference between hard skills and soft skills?
Hard skills are technical abilities learned through education or training, such as programming, data analysis, or laboratory testing. Soft skills refer to interpersonal abilities like communication, leadership, adaptability, and teamwork.
Why are professional skills important for careers and resumes?
Professional skills help employers evaluate whether a candidate can perform job responsibilities effectively. Listing relevant skills on a resume demonstrates qualifications and helps applications pass Applicant Tracking Systems used in modern hiring processes.
What professional skills do employers look for?
Employers usually value a combination of technical expertise and transferable workplace skills. Common examples include analytical thinking, communication, teamwork, leadership, time management, adaptability, and digital literacy.
How can professionals develop professional skills?
Professionals can develop skills through continuous learning, training programs, certifications, mentorship, and practical work experience. Staying updated with industry trends also helps individuals maintain relevant and competitive skills.
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Editorial operations are managed by Thanh Huyen, Managing Editor, with research direction and final oversight by Lam Nguyen, Founder & Editorial Lead. Content is periodically reviewed to reflect observable labor market changes.