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Senior Engineer / Lead Engineer – Virtual Engineering- AI ML

General Motors

Software and Technology Jobs

Senior Engineer / Lead Engineer – Virtual Engineering- AI ML

part-timePosted: Jan 15, 2026

Job Description

Description

Sponsorship:  GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE.  DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office three times per week or other frequency dictated by the business.

The Role

Senior Engineer / Lead Engineer – ML will leverage Machine Learning methodologies to improve Manufacturing Engineering and Operations processes. Execute end-to-end projects from ideation to deployment, applying relevant Tools and Methods in ML and data analytics to solve Manufacturing problems while ensuring data security and delivering measurable impact.

What You'll Do

  • Collaborate with stakeholders to understand business problems in the in the Manufacturing Engineering and Operations space and solve them using ML methodologies.

  • Design, develop, and fine-tune AI/ML models for classification, regression, clustering, and recommendation systems.

  • Work with MLOps tools to automate workflows, CI/CD pipelines, and model monitoring.

  • Evaluate, validate, and benchmark model performance using appropriate metrics.

  • Deploy AI models into production environments in collaboration with IT/AI teams.

  • Establish monitoring and maintenance processes to ensure model accuracy over time.

  • Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements.

  • Document workflows, results, and lessons learned for organizational knowledge sharing.

  • Stay updated on advancements in ML model evaluation, ML frameworks, end-to-end ML pipelines.

Your Skills & Abilities (Required Qualifications)

  • Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar.

  • 5+ years in Automotive Manufacturing / Manufacturing Engineering Experience.

  • 1+ year experience in implementing AI/ML solutions in Automotive use cases.

  • Should have executed at least 2 end-to-end projects in the text or Image data domain (from problem definition to deployment).

  • Strong programming skills in Python

  • Proficiency with ML/DL frameworks like Scikit-learn, TensorFlow, PyTorch, XGBoost.

  • Solid understanding of statistics, probability, and linear algebra.

  • Experience in data preprocessing, feature engineering, ETL and Exploratory Data Analysis (EDA).

  • Experience with MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML)

  • Knowledge of ML model evaluation

  • Experience with SQL/NoSQL databases and handling large datasets.

  • Strong problem-solving and analytical mindset.

  • Understanding of data annotation tools and MLOps workflows.

  • Experience in domain-specific AI use cases (manufacturing, automotive, etc.).

What Will Give You A Competitive Edge (Preferred Qualifications)

  • Knowledge of deep learning architectures (CNNs, RNNs, Transformers).

  • Familiarity with cloud-based platforms (Azure, AWS).

  • Experience in distributed training and scaling ML on large datasets.

  • Strong problem-solving mindset and curiosity for AI innovation.

  • Ability to translate domain problems into AI solutions.

  • Collaboration skills to work with cross-functional teams.

  • Clear communication of technical concepts to non-technical stakeholders.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us 

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Total Rewards | Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us Careers.Accommodations@GM.com or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Locations

  • Bengaluru, Karnātaka

Salary

Estimated Salary Rangemedium confidence

2,000,000 - 3,500,000 INR / yearly

Source: AI Estimation

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Pythonintermediate
  • Scikit-learn, TensorFlow, PyTorch, XGBoostintermediate
  • statistics, probability, and linear algebraintermediate
  • data preprocessing, feature engineering, ETL, Exploratory Data Analysis (EDA)intermediate
  • MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML)intermediate
  • ML model evaluationintermediate
  • SQL/NoSQL databasesintermediate
  • data annotation toolsintermediate
  • MLOps workflowsintermediate

Required Qualifications

  • Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar. (experience)
  • 5+ years in Automotive Manufacturing / Manufacturing Engineering Experience. (experience)
  • 1+ year experience in implementing AI/ML solutions in Automotive use cases. (experience)
  • Should have executed at least 2 end-to-end projects in the text or Image data domain (from problem definition to deployment). (experience)
  • Strong programming skills in Python (experience)
  • Proficiency with ML/DL frameworks like Scikit-learn, TensorFlow, PyTorch, XGBoost. (experience)
  • Solid understanding of statistics, probability, and linear algebra. (experience)
  • Experience in data preprocessing, feature engineering, ETL and Exploratory Data Analysis (EDA). (experience)
  • Experience with MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML) (experience)
  • Knowledge of ML model evaluation (experience)
  • Experience with SQL/NoSQL databases and handling large datasets. (experience)
  • Strong problem-solving and analytical mindset. (experience)
  • Understanding of data annotation tools and MLOps workflows. (experience)
  • Experience in domain-specific AI use cases (manufacturing, automotive, etc.). (experience)

Preferred Qualifications

  • Knowledge of deep learning architectures (CNNs, RNNs, Transformers). (experience)
  • Familiarity with cloud-based platforms (Azure, AWS). (experience)
  • Experience in distributed training and scaling ML on large datasets. (experience)
  • Strong problem-solving mindset and curiosity for AI innovation. (experience)
  • Ability to translate domain problems into AI solutions. (experience)
  • Collaboration skills to work with cross-functional teams. (experience)
  • Clear communication of technical concepts to non-technical stakeholders. (experience)

Responsibilities

  • Collaborate with stakeholders to understand business problems in the in the Manufacturing Engineering and Operations space and solve them using ML methodologies.
  • Design, develop, and fine-tune AI/ML models for classification, regression, clustering, and recommendation systems.
  • Work with MLOps tools to automate workflows, CI/CD pipelines, and model monitoring.
  • Evaluate, validate, and benchmark model performance using appropriate metrics.
  • Deploy AI models into production environments in collaboration with IT/AI teams.
  • Establish monitoring and maintenance processes to ensure model accuracy over time.
  • Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements.
  • Document workflows, results, and lessons learned for organizational knowledge sharing.
  • Stay updated on advancements in ML model evaluation, ML frameworks, end-to-end ML pipelines.

Benefits

  • general: Total Rewards | Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions.

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General Motors logo

Senior Engineer / Lead Engineer – Virtual Engineering- AI ML

General Motors

Software and Technology Jobs

Senior Engineer / Lead Engineer – Virtual Engineering- AI ML

part-timePosted: Jan 15, 2026

Job Description

Description

Sponsorship:  GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE.  DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office three times per week or other frequency dictated by the business.

The Role

Senior Engineer / Lead Engineer – ML will leverage Machine Learning methodologies to improve Manufacturing Engineering and Operations processes. Execute end-to-end projects from ideation to deployment, applying relevant Tools and Methods in ML and data analytics to solve Manufacturing problems while ensuring data security and delivering measurable impact.

What You'll Do

  • Collaborate with stakeholders to understand business problems in the in the Manufacturing Engineering and Operations space and solve them using ML methodologies.

  • Design, develop, and fine-tune AI/ML models for classification, regression, clustering, and recommendation systems.

  • Work with MLOps tools to automate workflows, CI/CD pipelines, and model monitoring.

  • Evaluate, validate, and benchmark model performance using appropriate metrics.

  • Deploy AI models into production environments in collaboration with IT/AI teams.

  • Establish monitoring and maintenance processes to ensure model accuracy over time.

  • Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements.

  • Document workflows, results, and lessons learned for organizational knowledge sharing.

  • Stay updated on advancements in ML model evaluation, ML frameworks, end-to-end ML pipelines.

Your Skills & Abilities (Required Qualifications)

  • Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar.

  • 5+ years in Automotive Manufacturing / Manufacturing Engineering Experience.

  • 1+ year experience in implementing AI/ML solutions in Automotive use cases.

  • Should have executed at least 2 end-to-end projects in the text or Image data domain (from problem definition to deployment).

  • Strong programming skills in Python

  • Proficiency with ML/DL frameworks like Scikit-learn, TensorFlow, PyTorch, XGBoost.

  • Solid understanding of statistics, probability, and linear algebra.

  • Experience in data preprocessing, feature engineering, ETL and Exploratory Data Analysis (EDA).

  • Experience with MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML)

  • Knowledge of ML model evaluation

  • Experience with SQL/NoSQL databases and handling large datasets.

  • Strong problem-solving and analytical mindset.

  • Understanding of data annotation tools and MLOps workflows.

  • Experience in domain-specific AI use cases (manufacturing, automotive, etc.).

What Will Give You A Competitive Edge (Preferred Qualifications)

  • Knowledge of deep learning architectures (CNNs, RNNs, Transformers).

  • Familiarity with cloud-based platforms (Azure, AWS).

  • Experience in distributed training and scaling ML on large datasets.

  • Strong problem-solving mindset and curiosity for AI innovation.

  • Ability to translate domain problems into AI solutions.

  • Collaboration skills to work with cross-functional teams.

  • Clear communication of technical concepts to non-technical stakeholders.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us 

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Total Rewards | Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us Careers.Accommodations@GM.com or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Locations

  • Bengaluru, Karnātaka

Salary

Estimated Salary Rangemedium confidence

2,000,000 - 3,500,000 INR / yearly

Source: AI Estimation

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Pythonintermediate
  • Scikit-learn, TensorFlow, PyTorch, XGBoostintermediate
  • statistics, probability, and linear algebraintermediate
  • data preprocessing, feature engineering, ETL, Exploratory Data Analysis (EDA)intermediate
  • MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML)intermediate
  • ML model evaluationintermediate
  • SQL/NoSQL databasesintermediate
  • data annotation toolsintermediate
  • MLOps workflowsintermediate

Required Qualifications

  • Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar. (experience)
  • 5+ years in Automotive Manufacturing / Manufacturing Engineering Experience. (experience)
  • 1+ year experience in implementing AI/ML solutions in Automotive use cases. (experience)
  • Should have executed at least 2 end-to-end projects in the text or Image data domain (from problem definition to deployment). (experience)
  • Strong programming skills in Python (experience)
  • Proficiency with ML/DL frameworks like Scikit-learn, TensorFlow, PyTorch, XGBoost. (experience)
  • Solid understanding of statistics, probability, and linear algebra. (experience)
  • Experience in data preprocessing, feature engineering, ETL and Exploratory Data Analysis (EDA). (experience)
  • Experience with MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML) (experience)
  • Knowledge of ML model evaluation (experience)
  • Experience with SQL/NoSQL databases and handling large datasets. (experience)
  • Strong problem-solving and analytical mindset. (experience)
  • Understanding of data annotation tools and MLOps workflows. (experience)
  • Experience in domain-specific AI use cases (manufacturing, automotive, etc.). (experience)

Preferred Qualifications

  • Knowledge of deep learning architectures (CNNs, RNNs, Transformers). (experience)
  • Familiarity with cloud-based platforms (Azure, AWS). (experience)
  • Experience in distributed training and scaling ML on large datasets. (experience)
  • Strong problem-solving mindset and curiosity for AI innovation. (experience)
  • Ability to translate domain problems into AI solutions. (experience)
  • Collaboration skills to work with cross-functional teams. (experience)
  • Clear communication of technical concepts to non-technical stakeholders. (experience)

Responsibilities

  • Collaborate with stakeholders to understand business problems in the in the Manufacturing Engineering and Operations space and solve them using ML methodologies.
  • Design, develop, and fine-tune AI/ML models for classification, regression, clustering, and recommendation systems.
  • Work with MLOps tools to automate workflows, CI/CD pipelines, and model monitoring.
  • Evaluate, validate, and benchmark model performance using appropriate metrics.
  • Deploy AI models into production environments in collaboration with IT/AI teams.
  • Establish monitoring and maintenance processes to ensure model accuracy over time.
  • Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements.
  • Document workflows, results, and lessons learned for organizational knowledge sharing.
  • Stay updated on advancements in ML model evaluation, ML frameworks, end-to-end ML pipelines.

Benefits

  • general: Total Rewards | Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions.

Target Your Resume for "Senior Engineer / Lead Engineer – Virtual Engineering- AI ML" , General Motors

Get personalized recommendations to optimize your resume specifically for Senior Engineer / Lead Engineer – Virtual Engineering- AI ML. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Senior Engineer / Lead Engineer – Virtual Engineering- AI ML" , General Motors

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Answer 10 quick questions to check your fit for Senior Engineer / Lead Engineer – Virtual Engineering- AI ML @ General Motors.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.