An Artificial Intelligence (AI)/Machine Learning (ML) Engineer is a specialized professional who plays a pivotal role in developing and implementing algorithms and predictive models that enable machines to learn and make decisions with minimal human intervention. This role This role is technical and involves a strategic understanding of how AI/ML solutions can be integrated and leveraged within an organization.
Creativity, Critical Thinking, Customer Focus, Dependability, Detail Orientation, Leadership, Lifelong Learning, Mathematics, Problem-Solving, Professionalism, Reading, Science & Technology, Scheduling, Teamwork & Writing
Understands the fundamental concepts of machine learning, including supervised learning, unsupervised learning, reinforcement learning, and deep learning
Can apply machine learning algorithms to solve simple problems
Can independently design and implement machine learning solutions for complex problems
Proficient in at least one programming language, such as Python or R, and has a basic understanding of software design principles and algorithms
Can develop and maintain machine learning software applications
Can design, develop, and deploy scalable and maintainable machine learning software systems
Possesses a strong foundation in mathematics, including linear algebra, calculus, and probability
Can apply mathematical and statistical techniques to machine learning problems
Can independently analyze and interpret complex mathematical and statistical data in the context of machine learning
Can perform data cleaning, preparation, and exploration tasks
Can build and train basic machine learning models using existing libraries and tools
Can independently design, develop, and evaluate complex machine learning models
This involves the knowledge and comprehension of artificial intelligence and machine learning principles. It ranges from basic understanding of key concepts and algorithms to a deep, proficient grasp of complex AI/ML techniques and the ability to innovate in this field.
Basic knowledge of key AI/ML concepts, such as types of machine learning (supervised, unsupervised). Understanding of simple algorithms like linear regression
Competent in Python or R for basic tasks and analytics
Familiarity with data manipulation using Pandas or similar libraries
Expert in software engineering practices, capable of designing and developing robust, scalable, and efficient systems integrating AI/ML components
Basic data preprocessing skills, such as handling missing values and basic feature engineering
Advanced data manipulation skills, including complex feature engineering and experience with big data technologies
Mastery in data engineering, capable of designing and implementing sophisticated data pipelines and handling real-time data streams
This area involves the skills necessary for creating and assessing AI/ML models. It encompasses the ability to develop simple models and understand basic performance metrics, progressing to the expertise in building sophisticated, efficient, and ethically sound models, along with a deep understanding of model validation and interpretability.
Ability to develop and evaluate simple models. Basic understanding of model performance metrics
Developing more sophisticated models, including tuning hyperparameters
Good understanding of model validation techniques and bias-variance tradeoff
Expert in model development, capable of building highly accurate, efficient, and robust models
Deep understanding
of model interpretability and ethical implications
To be an AI/Machine Learning Engineer, you need a bachelor’s degree, with a master’s degree or doctorate often preferred depending on the opportunity. Other preferred and/or required certifications include: AWS Certified Solutions Architect – Associate, Microsoft Azure Fundamentals, Google Associate Cloud Engineer, IBM Applied AI Professional Certificate, Introduction to Machine Learning (Deeplearning.ai), Machine Learning Foundations with TensorFlow on Coursera, Practical Deep Learning for Coders, Natural Language Processing (NLP) with Python, Computer Vision with Python, Machine Learning Engineering for Production (MLOps).
Check out our Career Resources Directory to find programs in Indiana that offer opportunities to develop your skills. These include certificate and degree attainment, internship programs, and mentorship to help you prepare for a career in tech.
