A machine learning engineer (ML engineer) focuses on researching, building and designing self-running artificial intelligence (AI) systems to automate predictive models. Machine learning engineers design and create machine learning models capable of learning and making predictions. An ML engineer typically works as part of a larger data science team and will communicate with data scientists, administrators, data analysts, data engineers and data architects. They may also communicate with people outside of their teams, such as with IT, software development, and sales or web development teams, depending on the organization’s size. ML engineers act as a bridge between data scientists who focus on statistical and model-building work and the construction of machine learning and AI systems. The machine learning engineer role needs to assess, analyse and organize large amounts of data, while also executing tests and optimizing machine learning models and algorithms.
AI/ML Engineer roles and responsibilities:
Designing ML systems. Researching and implementing ML algorithms and tools. Selecting appropriate data sets. Picking appropriate data representation methods. Identifying differences in data distribution that affects model performance. Verifying data quality and performing data cleaning, Transforming and converting data science prototypes. Performing statistical analysis. Running machine learning tests. Using results to improve models. Training and retraining systems when needed. Extending machine learning libraries. Developing machine learning apps according to client requirements.