Machine Learning Engineer

at SmartJoules

Machine Learning Engineer

SmartJoules

Company

Home

Machine Learning Engineer

at SmartJoules

Posted by Saksham Dutta

3 - 5 yrs

₹8L - ₹12L / yr

Remote, Delhi, Gurugram, Noida

Skills

Machine Learning (ML)

Python

Big Data

Apache Spark

Deep Learning

Responsibilities:

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.
Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
To design and develop Machine Learning systems and schemes.
To perform statistical analysis and fine-tune models using test results.
To train and retrain ML systems and models as and when necessary.
To deploy ML models in production and maintain the cost of cloud infrastructure.
To develop Machine Learning apps according to client and data scientist requirements.
To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.

Technical Knowledge:

Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase.
Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark, Pandas, Numpy and related libraries.
Expert in visualising and manipulating complex datasets.
Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
Big data Technologies such as Hadoop stack and Spark.
Basic use of clouds (VM’s example EC2).
Brownie points for Kubernetes and Task Queues.
Strong written and verbal communications.
Experience working in an Agile environment.

Responsibilities:

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.
Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
To design and develop Machine Learning systems and schemes.
To perform statistical analysis and fine-tune models using test results.
To train and retrain ML systems and models as and when necessary.
To deploy ML models in production and maintain the cost of cloud infrastructure.
To develop Machine Learning apps according to client and data scientist requirements.
To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.

Technical Knowledge:

Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase.
Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark, Pandas, Numpy and related libraries.
Expert in visualising and manipulating complex datasets.
Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
Big data Technologies such as Hadoop stack and Spark.
Basic use of clouds (VM’s example EC2).
Brownie points for Kubernetes and Task Queues.
Strong written and verbal communications.
Experience working in an Agile environment.

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About SmartJoules

Founded :

2015

Type :

Product

Size :

100-500

Stage :

Profitable

About

Energy efficiency is the cleanest, quickest and cheapest way to bring more than 300 million Indians out of energy poverty.
By eliminating waste in their own operations, building owners can save money, simplify operations, improve comfort and free up resources for the less fortunate. Smart Joules makes this process seamless and profitable from day one.

Connect with the team

Arjun Gupta

Anjali Yadav

Amit Phulera

Tanmay .

Arushi Chaudhary

Krishna R

Abhishek Khatri

Saksham Dutta

Mohit .

Company social profiles

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