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Machine Learning Engineer - AI Research (PhD) - Early Career
Machine Learning Engineer - AI Research (PhD) - Early CareerGeneral Motors • Mountain View, CA, United States
Machine Learning Engineer - AI Research (PhD) - Early Career

Machine Learning Engineer - AI Research (PhD) - Early Career

General Motors • Mountain View, CA, United States
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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 any other frequency dictated by the business.

Location :

Mt. View, California - Mountain View Technical Center

About the Team :

Our AI Research team, reporting directly to the Chief AI Officer, is pioneering how cutting-edge machine learning can transform the way vehicles are designed, manufactured, and experienced. We are building the next generation of intelligent systems—integrating multimodal foundation models, generative AI, robotics and predictive maintenance into real-world automotive innovation at global scale.

The Role :

As a Machine Learning Engineer, you will contribute to the development of end-to-end AI / ML systems that solve high-stakes problems in robotics and manufacturing at scale. You will work closely with senior engineers and researchers to design, prototype, and deploy state-of-the-art AI models with direct application to vehicle design, manufacturing operations, robotics, and simulation of physical systems. You will have the opportunity to translate cutting-edge research into production systems, collaborate with a world-class team of scientists and engineers, and grow your expertise while contributing to GM's AI research agenda and engaging with the broader AI community.

What You’ll Do :

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

Required Qualifications :

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

Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.

The salary range for this role is $130,000 - $170,,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Bonus Potential : An incentive pay program offers payouts based on company performance, job level, and individual performance.

What you’ll get from us (Benefits) :

GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

This job may be eligible for relocation benefits.

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