Job
Description
Overview:
In-depth understanding of the Python software development stacks, ecosystems, frameworks and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn and PyTorch.
Experience with popular Python frameworks such as Django, Flask or Pyramid.
Knowledge of data science and machine learning concepts and tools.
A working understanding of cloud platforms such as AWS, Google Cloud or Azure.
Contributions to open-source Python projects or active involvement in the Python community.
Experience with front-end development using HTML, CSS, and JavaScript.
Familiarity with database technologies such as SQL and NoSQL.
Excellent problem-solving ability with solid communication and collaboration skills.
Analyzing the ML algorithms that could be used to solve a given problem
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
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
Proficiency with a deep learning framework
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
Responsibilities:
Responsible for designing, developing, automating, and maintaining software applications, participating in all phases of the software development lifecycle (SDLC).
Requirements:
In-depth understanding of the Python software development stacks, ecosystems, frameworks and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn and PyTorch.
Experience with popular Python frameworks such as Django, Flask or Pyramid.
Knowledge of data science and machine learning concepts and tools.
A working understanding of cloud platforms such as AWS, Google Cloud or Azure.
Contributions to open-source Python projects or active involvement in the Python community.
Experience with front-end development using HTML, CSS, and JavaScript.
Familiarity with database technologies such as SQL and NoSQL.
Excellent problem-solving ability with solid communication and collaboration skills.
Analyzing the ML algorithms that could be used to solve a given problem
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
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
Proficiency with a deep learning framework
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
