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The specific areas of expertise should include big data analytics, visualizations, biomarker data repository development, clinical decision support, bioinformatics, clinical research informatics, machine learning, clinical trials, and related areas.
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Develop state of the art LLM based automated rating systems leveraging the Scale ecosystem for customized training data. AWS or GCP) and developing machine learning models in a cloud environment.
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As a Senior Machine Learning engineer, you will work on the development and implementation of cutting edge machine learning algorithms, training sophisticated models, collaborating with product, engineering, and analytics teams, to build transformative developer AI products and services.
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We’re looking for an Associate Product Manager - New Grad to build intuitive ML-assisted tooling for generating human data, data quality measurement platforms, and delightful AI researcher-facing products.
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Machine Learning: PyTorch, TensorFlow. This role offers the opportunity to work on innovative projects, build large-scale low-latency systems and state-of-the-art machine learning models, and significantly impact our Pinners and business metrics.
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Founded in late 2020 by a small group of machine learning researchers, Mosaic AI enables companies to create state-of-the-art AI models from scratch on their own data. Summary:Databricks is hiring a Senior Staff Machine Learning Engineer to play a key role in building our Generative AI platform and products, and in developing our team of software engineers.
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Databricks is hiring a Senior Staff Machine Learning Engineer to play a key role in building our Generative AI platform and products, and in developing our team of software engineers. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
$313,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Be responsible for the team that will architect, build, and design our tooling, infra, products, and evals that power our data collection and management platform, including collecting important training signals from products like ChatGPT, Dall-E, Sora, along with the key interfaces used by our AI human labelers.
$310,000 - $465,000 (equity)Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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This includes services to train and serve generative AI and machine learning models using novel data-centric techniques, libraries to support AI workflows for a variety of data modalities and task types, core training data management technologies, and more.
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The RoleWe're looking for a strong engineering tech lead and people manager to design and operate end-to-end hardware processes that produce high quality data for Zitara’s machine learning model training and algorithms testing.
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You will have the opportunity to build and maintain the infrastructure that fuels our machine learning algorithms, ensuring that the data is accurate, accessible, and ready to use for model training.
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Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
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Experience in connecting machine learning model behavior to data distribution and data quality. Optimizing training data quality and data mixture to improve evaluation metrics.
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You will be responsible for building the data and Machine Learning systems underpinning a user-friendly web app powered by our ML algorithms. Collaborating with our data scientists and machine learning engineers to integrate feedback.
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Continued success depends on building scalable, efficient and user-friendly machine learning training and data systems, generating billions-parameter models from petabytes of data every hour, to identify the most relevant ads.
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training machine learning data quality jobs in San Francisco, CA, Us
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