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