Machine Learning Scientist - LLM

March 27

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SES AI Corp

Renewable Energy, UAV, Electrical Manufacturing, Wearables, Electric Vehicles, Batteries, Li-Ion, Li-Metal, Drones, HAPS, Electrochemistry, Smartphones β€’ eVTOL β€’ EV

201 - 500

Description

β€’ Lead cutting-edge research in machine learning for scientific discovery, with a focus on (multimodal) large language models and their application (including AI agent) in battery and material discovery. β€’ Troubleshoot and optimize the training process of large language models, addressing the complexities and challenges inherent to training such sophisticated systems. This includes identifying and resolving issues related to data quality, model architecture, and computational efficiency, as well as implementing innovative solutions to enhance model performance and scalability. β€’ Design, develop, and deploy robust machine learning models in production environments, ensuring their scalability and reliability in collaboration with other computational teams. β€’ Foster collaboration with cross-functional teams across our AI team and other teams at SES, aiming to solve complex problems in battery and material sciences. β€’ Engage with external scientific partners, including top academic institutions and industry research groups, to drive innovation and research. Endeavor to publish research findings in top-tier machine learning conferences and journals.

Requirements

β€’ MS or PhD in Computer Science, Statistics, or a related field, or equivalent practical experience. β€’ At least 5 years of strong academic and industry experience in machine learning and natural language processing, with a preference for candidates who have focused on large language models and AI agents. β€’ 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. β€’ Proficient in programming languages relevant to machine learning, with a strong preference for Python. β€’ Experience with deep learning frameworks such as PyTorch or Tensorflow etc. β€’ An extensive track record of delivering innovative solutions in machine learning. β€’ Exceptional communication skills, capable of conveying complex technical concepts to a broad audience, including both technical and non-technical stakeholders. β€’ Demonstrated ability to collaborate effectively with external scientific partners.

Benefits

β€’ Remote position

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