Role: Artificial Intelligence Engineer
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At least 4-8 years hands-on experience working on enterprise IOT
and connected products.
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An expert in machine learning to help us extract value from the
data. Need to work on all the processes from data collection, cleaning, and pre-processing,
to training models and deploying them to production.
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The ideal candidate will be passionate about artificial
intelligence and stay up to date with the latest developments in the field.
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Understanding business objectives and developing models that help
to achieve them, along with metrics to track their progress.
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Managing available resources such as hardware, data, and personnel
so that deadlines are met.
· Analyzing the ML algorithms that could be used to solve a given
problem and ranking them by their success probability.
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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.
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Verifying data quality, and/or ensuring it via data cleaning.
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Supervising the data acquisition process if more data is needed.
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Finding available datasets online that could be used for training.
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Defining validation strategies & data augmentation pipelines.
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Defining the pre-processing or feature engineering to be done on a
given dataset.
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Training models and tuning their hyper parameters.
· Analyzing the errors of the model and designing strategies to
overcome them.
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Build data ingest and data transformation infrastructure.
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Build AI models from scratch and help stakeholders understand
results.
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Create APIs and help business customers put results of your AI
models into operations.
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Good to have embedded hardware and software knowledge on Internet
of Things.
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Demonstrated proficiency in multiple programming languages with a
strong foundation in a statistical platform such as Python, R, SAS, or MatLab.
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Experience building AI models in platforms such as Keras,
TensorFlow, or Theano.
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Proficiency with Python and basic libraries for machine learning
such as scikit-learn and pandas.
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Expertise in visualizing and manipulating big datasets.
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Proficiency with OpenCV and with Linux.
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Ability to select hardware to run an ML model with the required
latency.
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Must be intimately familiar with Agile and Scrum, in the creation
of dashboards for Sprints. An expectation would be to implement Scrum within
the organization.
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