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AI Research Scientist (Paris)

Min Experience

2 years

Location

Paris, hybrid

JobType

full-time

About the job

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About the role

AryaXAI stands at the forefront of AI innovation, revolutionizing AI for mission-critical businesses by building explainable, safe, and aligned systems that scale responsibly. Our mission is to create AI tools that empower researchers, engineers, and organizations to unlock AI's full potential while maintaining transparency and safety. Our team thrives on a shared passion for cutting-edge innovation, collaboration, and a relentless drive for excellence. At AryaXAI, everyone contributes hands-on to our mission in a flat organizational structure that values curiosity, initiative, and exceptional performance. As a research scientist at AryaXAI, you will be uniquely positioned in our team to work on very large-scale industry problems and push forward the frontiers of AI technologies. You will become a part of the unique atmosphere where startup culture meets research innovation, with key outcomes of speed and reliability. Responsibilities: - You'll work on advanced problems related to AI explainability, AI safety, and AI alignment. - You'll have flexibility in picking up the specialization areas within ML/DL and problem types that address the above challenges. - Create new techniques around ML Observability & Alignment. - Collaborate with MLEs and SDE to roll out the features and manage their quality until they are fully stable. - Create and maintain technical and product documentation. - Publish papers in open forums like arxiv and present in industry forums like ICLR NeurIPS etc.

About the company

AryaXAI stands at the forefront of AI innovation, revolutionizing AI for mission-critical businesses by building explainable, safe, and aligned systems that scale responsibly. Our mission is to create AI tools that empower researchers, engineers, and organizations to unlock AI's full potential while maintaining transparency and safety.

Skills

ml
deep learning
reinforcement learning
tensorflow
pytorch
mlops