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We are seeking a highly motivated Machine Learning Engineer Co-Op from July 2024 to December 2024, focusing on Natural Language Processing (NLP) and Computer Vision applications. As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
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We are currently sourcing for a Lead Software Engineer, Machine Learning to work at Fidelity Investments. As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines.
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Distinct experience in big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP.This is a hands-on leadership role which involves leading machine learning teams, building best architectural solutions, mentoring and imparting knowledge about machine learning and data concepts and techniques, as well as driving adoption of standards, processes, and tools to achieve high operational efficiency.
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They are reducing the cost of building LLM. They are hiring a Founding Machine Learning engineer. Their model router comes out of NLP research and they raised $9M from the likes of General Catalyst (Stripe, Airbnb) and NEA (Databricks, Salesforce.
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Expertise in scientific programming languages (e.g., Python, R) and machine learning libraries (e.g., PyTorch, Tensorflow) We seek an enthusiastic and collaborative machine learning scientist with a focus on AI/ML methods to join our Small Molecule Drug Discovery team.
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Working alongside our generalist consultants, Bain's Advanced Analytics Group (AAG) helps clients across industries solve their biggest problems using our expertise in data science, customer insights, statistics, machine learning, data management, supply chain analytics and data engineering.
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The team leverages its experience in the fields of signal processing, computer vision, computational linguistics, machine learning, artificial intelligence, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.
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We are growing a team of people from multiple disciplines who love solving complex problems with data and are excited by the prospect of creating the brains behind Iris. As a Machine Learning Engineer, you will be responsible for building the infrastructure and implementing the algorithms that make Iris smart.
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Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology. Ph. D. degree in Computer Science, Machine Learning or a related field.
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The Human-centered AI team in Digital Health Oncology R&D is looking for an Associate Director of Data Science to specialize in the development of novel digital endpoints using data science, statistical learning, and innovative machine learning methods on multi-modal datasets including clinical data, real world evidence, imaging, wearables, and other biomedical data sources to address patient burden.
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Familiarity with modern deep learning architectures including CNN, RNN, Transformer, GCNN and MPNN, and machine learning paradigms such as generative models, GAN, and active learning.
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Knowledge of statistical sampling, optimization, machine learning, predictive modeling, and artificial intelligence techniques. The Client Quantitative Analyst position is within the Client Protection organization supporting functions, including Fraud Prevention and Detection, Anti-Money Laundering (AML), Sanctions and Screening Compliance.
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Key medicinal chemistry principles to your cross-disciplinary colleagues from Computational Chemistry, AI Research, Machine Learning Engineering, Cell Biology, and Pharmacology. Key medicinal chemistry principles to your cross-disciplinary colleagues from Computational Chemistry, AI Research, Machine Learning Engineering, Cell Biology, and Pharmacology.
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You will push the boundaries of machine learning in the autonomous driving industry by developing state-of-the-art techniques in self-supervised learning, semi-supervised learning, multi-task learning, and generative models.
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Experience with any of the following Frameworks: Spring, Django, R Shiny, Tensorflow, MXNet Understanding or Application of Machine Learning and / or Deep Learning Experience in a scientific environment.
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machine learning jobs Title: engineer Company: Amazon Corporate Llc in Boston, MA
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