Work with ML problems end-to-end, starting from the ideation phase to full-scale deployment in production environments.
Work closely with Data scientists and other engineering teams in scaling, productionalizing and maintaining ML models.
Build robust data pipelines.
Dig deep into data, clean it, establish data stores if not existent.
Do the independent analysis, validate hypothesis, set up evaluation metrics.
Test out different architectures, new algorithms and platforms.
Build quick proof of concepts.
Must Haves :-
An engineering degree in computer science or related fields.
2+ years of experience in a hands-on development role preferably in an ML / Data Science / Data Engineering environment.
In-depth understanding of machine learning algorithms.
Solid coding skills in Java or Scala.
Knowledge of data structures and algorithms.
Experience in building end-to-end data and ML pipelines.
Ability to work with unstructured problems and take end-to-end ownership of projects.
Experience in python with exposure to frameworks such as TensorFlow, PyTorch, OpenCV, MXNet, Spark MLLib; Exposure to big data tools like Spark, Flink, Hadoop and Hive.
The eagerness to learn and experiment.
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