Faculty for The Machine Learning - Ernakulam, India - ROGERSOFT Technologies Pvt Ltd

ROGERSOFT Technologies Pvt Ltd
ROGERSOFT Technologies Pvt Ltd
Verified Company
Ernakulam, India

1 week ago

Deepika Kaur

Posted by:

Deepika Kaur

beBee Recuiter


Description
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.


Responsibilities:

Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress

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

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


Skills:

Proficiency with a deep learning framework such as TensorFlow or Keras

Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas

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


Salary:
Up to ₹15,000.00 per month


Ability to commute/relocate:

  • Ernakulam, Kerala: Reliably commute or planning to relocate before starting work (required)

Experience:

- total work: 1 year (preferred)


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