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Skilled in machine learning libraries (Sklearn, TensorFlow API) and data visualization tools (Power BI, Tableau, R-Shiny). Minimum 5 years of experience in Data Science, Data Engineering, or a closely related field, with a focus on using open-source software and Docker in a production environment.
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Experience with machine learning related open source libraries including, but not limited to: Hadoop, Spark, SciKit-Learn, TensorFlow, etc. We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Experience with natural language processing, text mining, or machine learning techniques and building engineering code using open source programming languages, including Python, R, or JavaScript.
$106,200 - $242,000 a yearFull-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture design.
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Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Participating in INT Functional Management meetings related to Open-source intelligence (OSINT), Measurement and Signature Intelligence (MASINT), and Human Intelligence (HUMINT), as well as ISR Collection, ISR capabilities and ISR Data Integration tasks related to IC and International partnership.
$100,000 - $120,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The position aims for candidates with a strong quantitative and computational background with extensive experience in genomics/transcriptomics (analysis of different bulk/single cell/spatial Next Generation sequencing Techniques as well as development of novel methods.
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Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Machine Learning is an integral part of how we design products, operate, and pursue Cash App’s mission to serve the unbanked as well as disrupt traditional financial institutions.
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Our data engineering team leverages open-source scripting and data visualization tools to wrangle, clean, analyze and display data in decision support tools for senior leaders within the Department of Defense.
$96,000 - $144,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The successful candidate will perform integrative analysis of diverse data types, develop and utilize next generation sequencing (NGS) and other analytical pipelines, and collaborate with internal and external investigators for interpretation of high dimensional data sets to inform biomarker hypotheses, target discovery, and other biological queries.
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This team has tremendous learning opportunities including data-centric AI, deployment, and open source community contribution. Familiarity with open source LLM ecosystem such as Hugging Face and LangChain.
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Work cross-functionally with product, platform, security, and data engineering teams to unlock new machine learning applications. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture designAbility to align AI/ML initiatives with broader business goals and outcomes, understanding how AI can drive value and competitive advantage.
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Strong background in platforms and tools such as OpenAI, Azure Semantic Kernel, AWS Bedrock, and other machine learning technologies, with a focus on Generative AI and open-source AI frameworks.
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Familiarity with cloud platforms that offer specific support for deploying and scaling generative models, such as Google's Vertex AI, Azure's AI tools, and AWS's Machine Learning services.
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