SES AI Corp · 2 days ago

Machine Learning Scientist

United States

Full-time

Remote

Senior Level

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BatteryElectric Vehicle

Hiring Manager

Brian Moore

Insider Connection @SES AI Corp

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Responsibilities

Design and develop advanced deep learning models, including graph neural networks, to accurately predict the chemical properties of battery materials.

Lead innovative projects in generative model development, utilizing reinforcement learning, VAE, GANs, and stable diffusion models to create new battery material compositions.

Develop machine learning/deep learning-based models to approximate density function theory calculations (DFT).

Collaborate with a multidisciplinary team of scientists and engineers to integrate machine learning methods into the battery discovery process.

Stay abreast of the latest advancements in machine learning and computational chemistry to continuously improve model performance and discovery methodologies.

Contribute to academic and industry discussions by publishing research findings in top-tier journals and presenting at conferences.

Qualification

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Deep LearningGraph Neural NetworksReinforcement LearningVariational AutoencoderGenerative Adversarial NetworksDiffusion ModelsPublication RecordMachine Learning DevelopmentPythonPyTorchTensorFlowAnalyticalProblem-SolvingInnovativeComputational ChemistryPhysicsMaterial Science

Required

Advanced degree (Ph.D. preferred) in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Strong foundation and proven track record in deep learning, graph neural networks, reinforcement learning, variational autoencoder, generative adversarial networks and diffusion models.

Have a distinguished history of contributing to the field through publications in leading machine learning conferences and journals, such as ICLR, NeurIPS, ACL, ICML, CVPR, and Nature Machine Intelligence.

Demonstrated experience in developing and implementing machine learning models for scientific or industrial applications.

Proficiency in programming languages and frameworks relevant to machine learning such as Python, PyTorch, and TensorFlow etc.

Exceptional analytical and problem-solving skills, coupled with a strong passion for research and innovation in machine learning.