Senior Engineer / Lead Engineer – Virtual Engineering- AI ML at General Motors

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

NoVisa

Automotive, ManufacturingIndustries

Requirements

Bachelor’s or Master’s Degree in 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.)

Responsibilities

Collaborate with stakeholders to understand business problems 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
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

Skills

Machine Learning

AI/ML Models

MLOps

CI/CD Pipelines

Model Monitoring

Classification

Regression

Clustering

Recommendation Systems

Data Analytics

Model Deployment

Data Security

Manufacturing Engineering

General Motors

Designs, manufactures, and sells vehicles

About General Motors

General Motors designs, manufactures, and sells vehicles and vehicle parts, catering to individual consumers, businesses, and government entities. The company operates in both traditional internal combustion engine vehicles and the growing electric vehicle (EV) market, generating revenue through vehicle sales and financing services. GM stands out from competitors with its commitment to community service, sustainability, and diversity, as evidenced by a majority female Board of Directors. The company's goal is to balance traditional automotive manufacturing with technological advancements in electric and autonomous vehicles.

Detroit, MichiganHeadquarters

1908Year Founded

$486.7MTotal Funding

IPOCompany Stage

Automotive & Transportation, Financial ServicesIndustries

10,001+Employees