Artificial Intelligence (A.I)
Level 1
Description
- Responsible for the MLOps pipelines creation and automation on cloud and on premise, CI/CD pipelines orchestration ML models deployment, testing and continuous maintenance
- Optimises the code and make sure that the ML application is scalable
- Data scientist code refactoring
- Communicate with the project team
- Take offline models data scientists build and turn them into a real machine learning production system
- Identifies and evaluate new technologies to improve performance, maintainability and reliability of the machine learning systems
- Applies software engineering rigour and best practices to machine learning, including CI/CD automation
- Supports model development, with an emphasis on auditability, versioning, and data security
- Facilitates the development and deployment of proof-of-concept machine learning systems
Required Skills
- Report writing skills to convey technical information and findings, provide the details about the processes and objectives, and describe the design choices and products
- Communication skills and the ability to translate technical concepts into simple language in an engaging and confident manner
- Listening skills to understand problems and issues clearly
- Leadership skills if in the management role and capacity
- Designs and develop algorithms that can adapt and learn over time as they process large amounts of data
- Applies data science principles to engineering and use various programming languages to develop software! solutions that meet project requirements
- Works with data scientists, product managers, customers and machine learning experts to develop applications that solve real world problems
- Converts Al/ML models into APIs that other developers can use
- Performs statistical analysis on big data sets
- Specifies infrastructure requirements and environment required to
execute the Al Project
- Mastering one or more of the programming languages used in AI, for example Python, R and Java
- Able to perform all processes of data science including but not limited to the following:
- Frame the problem
- Collecting the raw data
- Process the data for analysis
- Explore the data
- Perform in-depth analysis
- Communicate the results of the analysis
- Able to perform app processes of machine learning, including but not limited to the following:
- Data gathering
- Data preparation
- Model selection
- Training Model evaluation
- Hyperparameter
- Tuning Prediction
ETL Processes
Python
Machine learning
Big Data
Common Tools
- Familiarity with one or more of the popular machine learning frameworks e.g. TensorFlow, PyTorch and JAX
- Able to perform all processes of data science including but not limited to the following:
- Frame the problem
- Collecting the raw data
- Process the data for analysis
- Explore the data
- Perform in-depth analysis
- Communicate the results of the analysis
- Able to perform app processes of machine learning, including but not limited to the following:
- Data gathering
- Data preparation
- Model selection
- Training Model evaluation
- Hyperparameter
- Tuning Prediction
Career Pathways
Senior AI Developer
AI Application Developer
Associate AI Application Developer
Common Certifications
Bachelor or Postgraduate degrees in AI or Machine Learning or STEM (Science, Technology , Engineering and Mathematics)
Machine learning and AI courses from reputable universities
Professional Certificates of Python, R and Other Machine learning Courses
Other Career Roles
Explore detailed career information and progression paths
Level 4
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ISO Certification
Team Building
Communication
Level 1
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ETL Processes
Python
SQL
Big Data
Level 3
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ISO Certification
Team Building
Communication
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