Senior Machine Learning Engineer - AI Research at General Motors

Mountain View, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Automotive, AI Research, ManufacturingIndustries

Requirements

PhD in a relevant field or related discipline (STEM focused)
Post PhD or equivalent industry experience in AI/ML research and applied development, demonstrating advanced expertise in designing and implementing modern machine learning systems
Expert level knowledge about modern deep learning architectures and techniques including Transformers, Diffusion Models, CNNs with hands-on experience training large-scale models
Proficiency with leading ML frameworks such as PyTorch, TensorFlow, JAX, or Keras, and strong software engineering practices for scalable, efficient experimentation
Strong programming skills in Python, with working knowledge of at least one systems language (e.g., C++ or Java)
Demonstrated track record of publications in top AI/ML conferences or patents demonstrating novel contributions to the field
Ability to decompose ambiguous problems into tractable research questions and follow rigorous experimental methodology including hypothesis formation, data collection, evaluation and statistical analysis
Preferred Qualifications
Experience developing AI systems for anomaly detection, fault diagnosis, or predictive maintenance in complex environments (e.g., automotive, manufacturing, robotics, or industrial systems)
Hands-on experience with reinforcement learning, particularly for robotic control, simulation-to-real transfer, or large-scale process optimization
Proven ability to train and optimize large-scale multimodal deep learning models, integrating modalities such as vision, language, and sensor data
Demonstrated research or applied innovation impact through publications at top-tier AI/ML venues (e.g., NeurIPS, ICML, CVPR, ICRA) or contributions to production-grade, industry-leading AI systems

Responsibilities

Design and implement novel machine learning architectures for complex industrial applications, including computer vision, robotic manipulation, predictive maintenance, and process optimization
Develop end-to-end deep learning pipelines that handle multi-modal sensor data (vision, force/torque, proprioception, environmental sensors)
Create foundation models and transfer learning frameworks that generalize across diverse industrial scenarios and equipment types
Collaborate with cross functional teams including robotics engineers, SMEs and product teams to understand requirements and translate those to develop ML systems for production systems
Develop data collection and annotation strategies to build high quality datasets for training and validating models in industrial settings
Stay current with state-of-the-art methods in ML/AI and share knowledge through internal tech talks and presentations

Skills

Machine Learning

Deep Learning

Computer Vision

Robotics

Predictive Maintenance

Foundation Models

Transfer Learning

Multi-modal Data

Sensor Data

Data Annotation

PyTorch

TensorFlow

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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