Machine Learning Engineer- GPU
il y a 4 semaines
As a Machine Learning Engineer- GPU at Bioptimus, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms. You will work with interdisciplinary teams with both machine learning and biomedical expertise to build foundation models of biology that will unlock AI applications in biomedical innovation.In particular, you will:As an expert Machine Learning Engineer- GPU with experience in large-scale deep learning, you will:Join a team setting the foundations and paving the way for the development and application of foundation models in biomedical researchDrive the implementation and application of advanced machine learning methods, in particular in foundation models, representation learning, large language models and generative AI, to relevant internal and external projectsContribute to methodological research in key areas to unlock novel applications in collaboration with research scientists.Depending on your level of experience, you will have the opportunity to supervise a team and lead ambitious projects.Who we are looking for:The successful Machine Learning Engineer- GPU will have a ‘team-first’ kind of attitude; be independent, curious and detail-attentive; thrive in a dynamic, fast-paced environment; and be fun to work with.Expert in crafting high-performance CUDA kernels to unleash the full potential of GPUs. Possesses deep knowledge of distributed computing frameworks for managing current-generation GPU clusters.Extracting maximum performance from modern GPUs (like H100) for efficient model inference and training, by crafting low-level code and redesigning architectural elements.Integrating low-level efficient code in a high-level MLOps frameworkOverall understanding of the field of generative AI, knowledge or interest in fine-tuning and using language models for applicationsDemonstrated practical expertise in representation learning/large language models/generative AI, including prior experience of implementing, training and/or deploying large neural networksStrong analytical skillsExcellent command of coding in python, and excellent grasp of programming best practicesPassionate about the intersections of healthcare/biology and AIMSc or PhD in Computer Science-related field (machine learning, applied mathematics, computer science, software engineering) or equivalent experience;Strong expertise with deep learning frameworks (Tensorflow, PyTorch, Jax, etc.): you should already master one of these frameworks and implemented large neural networks in an industrial environment or equivalentExcellent written and oral communication skillsHighly organized and meticulous about details; capable of tackling complex problems logically and effectivelyWays to stand out:The following are not necessarily required, but would be a plus for the Machine Learning Engineer- GPU:Experience in biological data analysis: proteins, bulk or single-cell omics, histopathology, etcExtensive post-master or good level of post-doctoral experience; or the equivalent experience industry experienceExperience managing multi-stakeholder research projectsPublications in high-impact journals (JMLR, TMLR, ...) and conferences (NeurIPS, ICLR, ICML, …) #J-18808-Ljbffr
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Machine Learning Engineer- GPU
il y a 1 jour
Paris, Île-de-France Bioptimus Temps pleinAs a Machine Learning Engineer- GPU at Bioptimus, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms. You will work with interdisciplinary teams with both machine learning and biomedical expertise to build foundation models of biology that will unlock AI applications in biomedical innovation.In...
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Formation Machine Learning Engineer
il y a 4 semaines
Paris, France Bioptimus Temps pleinAs a Machine Learning Engineer- GPU at Bioptimus, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms. You will work with interdisciplinary teams with both machine learning and biomedical expertise to build foundation models of biology that will unlock AI applications in biomedical innovation.As an...
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Formation Machine Learning Engineer
il y a 4 semaines
Paris, Île-de-France Bioptimus Temps pleinAs a Machine Learning Engineer- GPU at Bioptimus, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms. You will work with interdisciplinary teams with both machine learning and biomedical expertise to build foundation models of biology that will unlock AI applications in biomedical innovation.As an...
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il y a 1 semaine
Paris, Île-de-France Barrington James Temps pleinI am partnering with a AI Driven Biotech startup based in the heart of Paris who are developing a generative AI Platform to discover new catalysts and molecules with the aim of disrupting carbon intensive industries. After a significant round of funding, they are looking to expand the team with senior hires in different areas of the business. Senior...
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il y a 2 semaines
Paris, Île-de-France Barrington James Temps pleinI am partnering with a AI Driven Biotech startup based in the heart of Paris who are developing a generative AI Platform to discover new catalysts and molecules with the aim of disrupting carbon intensive industries. After a significant round of funding, they are looking to expand the team with senior hires in different areas of the business. Senior...
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il y a 4 semaines
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il y a 1 jour
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il y a 1 semaine
Paris, Île-de-France Barrington James Temps pleinI am partnering with a AI Driven Biotech startup based in the heart of Paris who are developing a generative AI Platform to discover new catalysts and molecules with the aim of disrupting carbon intensive industries. After a significant round of funding, they are looking to expand the team with senior hires in different areas of the business. I am looking...
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Paris, Île-de-France Beelix Temps pleinQui sommes-nous ? Depuis 2016, nous accompagnons nos clients sur des problématiques de Product Management, Data et Design Thinking.Beelix contribue aux grandes avancées dans les secteurs suivants :AutomobileEnergieMédias & TélécomsLuxe & RetailBanque, Finance & AssuranceDéfenseAujourd'hui, Beelix compte plus de 250 collaborateurs motivés et...
