Experience: 3 year – 6 Years
Responsibilities:
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
- Managing available resources such as hardware, data, and personnel so that deadlines are met
- Develop and Analyze the ML algorithms that could be used to solve a given problem and ranking them by their success probability
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Verifying data quality, and/or ensuring it via data cleaning
- Finding available datasets online that could be used for training
- Defining validation strategies
- Defining the preprocessing or feature engineering to be done on a given dataset
- Defining data augmentation pipelines
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Deploying models to production
- Full Stack development for Production Systems
Skills:
- Proficiency with a deep learning framework such as TensorFlow or Keras
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Expertise in visualizing and manipulating big datasets
- Proficiency with OpenCV
- Familiarity with Linux
- Ability to select hardware to run an ML model with the required latency
- Proficiency in Full Stack Web Development