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Salary
$22k – $55k per year (Estimated)
Location
In office (Pune)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Intangles offers AI-powered fleet management with predictive maintenance, digital twin technology, vehicle health, fuel & EV monitoring, driving behavior, real-time data, and operations automation to maximize efficiency and reduce costs.

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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