Ml Engineer

Responsibilities:

• 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.

Skills and Experience:

• 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.