The Machine Learning (ML) Engineer is an expert on using data to train models used to automate processes like image classification, speech recognition, and market forecasting. He/She is a person in IT who focuses on researching, building and designing self-running artificial intelligence (AI) systems to automate predictive models.
Key Responsibilities
- Researches and implements Machine Learning algorithms and tools.
- Transforms data science prototypes and applies appropriate ML algorithms and tools.
- Understands and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture
- Designs self-running software to automate predictive models.
- Supervises the data acquisition process if more data is needed
- Identifies differences in data distribution that affect model performance.
- Turns unstructured data into useful information by auto-tagging images and text-to-speech conversions.
- Uses data modelling and evaluation strategy to find patterns and predict unseen instances
- Analyzes the errors of the model and designing strategies to overcome them
Job Requirements/Qualifications:
- Degree in computer science, mathematics, data science or other related fields
- Proven work experience as a Machine Learning Engineer
- Background in machine learning frameworks such as TensorFlow or Keras
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture
- Expertise in producing, processing, evaluating and utilizing training data.
Skills needed for this role
The Machine Learning (ML) Engineer must have exceptional mathematical skills, in order to perform computations and work with algorithms. He/She must have excellent written and verbal communication skills and the ability to explain complex process to people who aren’t programming experts
Career Level
More than 5 Years Experienced Employee
Job Specializations
Information and Technology