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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
Requirements:
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
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
Excellent communication skills
Bachelors or Masters from Premier Institutes preferred