Designing and developing machine learning and deep learning systems according to the requirements.
Analysing the ML algorithms that could be used to solve a given problem and ranking them by their success probability.
Independently handle bug fixes and releases to production
Verifying data quality, and/or ensuring it via data cleaning.
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.
Perform self-testing, integration testing and deployment testing.
Deployment of code to production environment following the procedures and standards diligently.
Explore and analyze the suitability of third-party libraries.
Deploying models to production.

Proven experience as a Machine Learning Engineer or similar role.
Understanding of data structures, data modelling and software architecture.
Deep knowledge of linear algebra, probability, statistics and ML algorithms.
Good knowledge of data structures and algorithms and implementing them in C/C++.
Working experience with device drivers on Linux specifically related to real-time video streaming pipeline using v4l2, Gstreamer, UVC driver, Nvidia accelerated Gstreamer, low latency video capture.
Ability to write robust code in Python, R and Java.
Knowledge of C Embedded programming is preferred.
Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like Numpy, pandas, seaborn, scikit-learn, etc.)
Proficiency with a deep learning framework such as TensorFlow or Keras.
Proficiency with OpenCV.
Linux SysAdmin skills.
Git management, source code build and release management.
Ability to select hardware to run an ML model with the required latency.
Experience in Image Processing is preferable.
Excellent communication skills.

Machine Learning Engineer