Machine Learning Engineer - AI Research at General Motors

Mountain View, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Automotive, ManufacturingIndustries

Requirements

PhD in relevant field or related discipline (STEM focused) or Masters degree with significant ongoing AI/ML contributions
In depth knowledge about modern deep learning architectures—Transformers, Diffusion Models, CNNs and model training techniques at scale
Strong hands-on experience with at least one of the popular AI/ML frameworks (PyTorch, Tensorflow, Keras or JAX)
Strong programming skills in Python and familiarity with one or more of systems languages (C++/Java)
Demonstrated track record of publications in top AI/ML conferences or patents demonstrating novel contributions to the field
Ability to formulate research questions from ambiguous problems and apply rigorous experimental methodology including hypothesis formation, evaluation, and statistical analysis
Able to work full time, 40 hours per week
Preferred Qualifications
Experience with anomaly detection and predictive maintenance applications through course work, research or projects
Experience with reinforcement learning for robotic control or process optimization through course work, research or projects
Experience training multimodal deep learning models
Demonstrated research contributions in AI/ML technologies through publication of PhD research in top-tier conferences or journals

Responsibilities

Adapt machine learning architectures for complex industrial applications, including computer vision, robotic manipulation, predictive maintenance, and process optimization
Build end-to-end deep learning pipelines that handle multi-modal sensor data (vision, force/torque, proprioception, environmental sensors)
Contribute to the development of foundation models and transfer learning frameworks that generalize across diverse industrial scenarios and equipment types
Contribute to the development of data collection and annotation strategies to build high quality datasets for training and validating models in industrial settings
Work with partner teams to translate technical requirements into ML solutions and support integration efforts
Own the deployment and monitoring of ML models in production environments
Publish research findings in top-tier venues (for example, NeurIPS, ICML, CVPR) and contribute to GM’s presence in the research community

Skills

Machine Learning

Deep Learning

Computer Vision

Robotics

Predictive Maintenance

Foundation Models

Transfer Learning

Multi-Modal Data

Data Annotation

Sensor Data Processing

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

Benefits

Paid Vacation

Paid Sick Leave

Paid Holidays

Parental Leave

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

401(k) Company Match

401(k) Retirement Plan

Tuition Reimbursement

Student Loan Assistance

Flexible Work Hours

Discount on GM vehicles

Risks

Shutting down Cruise Robotaxi may affect investor confidence in GM's AV strategy.

Chevrolet Equinox EV recall could harm GM's safety reputation.

Leadership transition in design may disrupt continuity and brand identity.

Differentiation

GM's Dynamic Fuel Management system enhances fuel efficiency in traditional vehicles.

GM leads in board diversity with 55% women directors.

GM's pivot to personal autonomous vehicles aligns with consumer trends.

Upsides

Partnership with Nvidia boosts GM's autonomous vehicle technology capabilities.

Collaboration with ChargePoint expands EV charging infrastructure, enhancing consumer appeal.

Bryan Nesbitt's appointment as design head may bring innovation to GM's vehicle design.

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