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AI Research Scientist
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Paris, France Lexsi Labs Temps pleinA pioneering AI research lab in Paris seeks an AI Research Scientist to work on advanced AI explainability, safety, and alignment problems. The role requires a Master's or Ph.D. in relevant fields and hands-on experience with deep learning frameworks like TensorFlow. Responsibilities include creating new techniques, collaborating on features, and publishing...
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Paris, France Lexsi Labs Temps pleinJoin to apply for the AI Research Scientist (PhD) role at Lexsi Labs The Lexsi Lab is a premier research lab dedicated to solving one of the most critical challenges of our time: ensuring that advanced artificial intelligence systems are safe, transparent, and aligned with human values. Founded by pioneers in the deep learning space, our lab operates at the...
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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 such as ICLR and NeurIPS. Qualifications Has a solid academic background in concepts of machine learning or deep learning or reinforcement learning. Master or Ph.D in key engineering topics such as computer science or mathematics is required. Should have published peer‑reviewed papers or contributed to open‑source tools. Hands‑on experience in working with deep learning frameworks like TensorFlow, PyTorch, etc. Enjoys working on various DL problems that involve using different types of training data sets – textual, tabular, categorical, images, etc. Comfortable deploying code in cloud environments/on‑premise environments. Good fundamentals in MLOps and productionising ML models. Prior experience working on ML explainability methods – LRP, SHAP, LIME, IG, CEM, etc. 2+ years of hands‑on experience in Deep Learning or Machine Learning. Hands‑on experience in implementing techniques like Transformer models, GANs, Deep Learning, etc. #J-18808-Ljbffr
