Job Summary:
Machine Learning (ML) Engineer – Design and development of machine learning models for analysis of
power train and vehicle dynamics data to serve use cases such vehicle health/performance management
and driver behavior monitoring. The job also entails research in statistics, mathematics and automobile
machinery/practices for evolution of hybrid algorithms which couple physics and machine learning. A
Senior ML engineer is also expected to work closely with a team of budding ML engineers and analysts in
evolving and validating new designs.
Job Responsibilities:
Primary:
Design and development of machine learning models for analysis of power train and vehicle dynamics
data. Research in the fields of statistics, mathematics and automobile-technology for evolution of hybrid
algorithms which couple physics and machine learning. Use cases for said hybrid data models vary across
vehicle health management, fuel pilferage tracking and driver behavior profiling.
Secondary:
Implementation of aforementioned models from a software development perspective. Working closely
with data engineering and GUI teams for deployment, usability and performance management of
algorithms. Interfacing with and enabling service teams with appropriate know-how to best address
queries pertaining to data models.
Skills and Qualifications:
-
BE/B Tech CE/IT OR Mtech in CE/IT/DataScience
-
1.5 - 4 years of experience into Machine Learning
-
Certification in Machine learning, AI, Deep Learning, Statistics, Data Mining
-
Languages: Python, R, Nodejs, Scala
-
Databases: MySQL(RDBMS), MongoDB, Timescale, InfluxDB
-
Tools and packages: Pandas, Matplotlib , Seaborn, Plotly, ggplot2 , Bokeh, OpenCV, Numpy,
Scipy, ScikitLearn, Statsmodels, TensorFlow
- Algorithms: Multi Variable Regression, Density Clustering, Support Vector Machines, Bayesian
Models, Decision Trees(XG Boosting, Random Forests), PCA
●Good communication & managerial skills.
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