Position Details

Salary $112K – $169K USD / year

Type Not Specified

Experience senior

Exp. Years Not stated

Education Bachelor's degree in accredited Mechanical, Electrical, or Computer/Data Science Engine

Category AI & Machine Learning

About this role

This role is a technical contributor for embedded product analytics projects in the Digital & Analytics team. The engineer will develop algorithms and analytical models using product data and deploy machine-learning models for engine and aftertreatment condition monitoring prioritized service events.

Key Responsibilities

Develop complex algorithms and analytical models
Build data mining processes and tools for engine analytics
Perform reliability/durability forecasting for engineering use cases
Create and deploy machine-learning-based Engine and Aftertreatment CM-PSE models
Partner with cross-functional teams and suppliers to deliver embedded analytics projects

Technical Overview

You will design and implement complex algorithms and data mining processes for engine data collection, aggregation, feature extraction, and analytics modeling. The role includes reliability/durability forecasting and deploying machine-learning-based Engine and Aftertreatment Condition Monitoring Prioritized Service Event (CM-PSE) models within agile and digital NPI processes.

Ideal Candidate

The ideal candidate is a senior embedded analytics engineer who can design complex algorithms and analytical models using product data from field and lab environments. They have strong machine-learning experience building Engine and Aftertreatment Condition Monitoring Prioritized Service Event (CM-PSE) models, with experience in reliability/durability forecasting and delivering analytics projects within agile and digital NPI processes.

Must-Have Skills

Embedded product analyticsDevelopment and design of complex algorithms and analytical modelsMachine-learning-based Engine and Aftertreatment Condition Monitoring Prioritized Service Event (CM-PSE) models

Tools & Platforms

machine learningagileembedded analytics

Required Skills

embedded analyticsalgorithmsanalytical modelsproduct data analysisdata miningfeature extractionanalytics modelingreliability/durability forecastingmachine learningcondition monitoringCM-PSEengine data collectiondata aggregationagiledigital NPIsimulationCPINPIembedded analytics project delivery

Hard Skills

embedded analyticsalgorithmsanalytical modelsproduct data analysisdata mining processesdata mining toolsengine data collectiondata aggregationfeature extractionanalytics modelingreliability/durability forecastingmachine-learning-based modelsengine data condition monitoringAftertreatment Condition Monitoring Prioritized Service Event (CM-PSE) modelsmodel validation and implementationsimulationCPINPIagile and digital NPI processesembedded analytics project delivery

Soft Skills

technical collaborationcommunicating technical information clearlypartnering with cross-functional teamsguiding less experienced engineersinnovation mindset

Industry & Role

Industry Manufacturing

Job Function Develop and deploy embedded machine-learning analytics models for engine and aftertreatment condition monitoring and prioritized service events.

Role Subtype ML Engineer

Tech Domains AI & Machine Learning

Keywords for Your Resume

Embedded Product Analytics Senior EngineerEmbedded analyticsembedded analytics projectsalgorithmsanalytical modelsproduct datafield and labdata miningfeature extractionanalytics modelingreliability/durability forecastingsimulationCPINPImachine learningmachine-learning-basedEngine and Aftertreatment Condition Monitoring Prioritized Service Event (CM-PSE)condition monitoringagiledigital NPIEmbedded Product AnalyticsAftertreatment Condition Monitoring Prioritized Service Event (CM-PSE)

Deal Breakers

Must have a Bachelor's degree in accredited Mechanical, Electrical, or Computer/Data Science Engineering

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