Machine Learning Engineer

Job Overview:

We are looking for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.

Responsibilities:

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.
• Create machine learning systems using analytics, performance and monitoring, running tests and experiments as required.
• Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability.
• Deploy forecasting algorithms that affect pertinent KPIs.
• 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.
• 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.

Requirements:

• Proven experience as a Machine Learning Engineer or similar role.
• Understanding of data structures, data modeling and software architecture.
• Deep knowledge of math, probability, statistics and algorithms.
• Proficiency with a deep learning framework such as TensorFlow or Keras.
• 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.
• Ability to write robust code in Python, Java and R.
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
• Excellent communication skills.
• Ability to work in a team.
• Outstanding analytical and problem-solving skills.

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