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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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The ideal candidate will have extensive experience in deep learning and NLP, specifically with advanced models such as GPT-3, BERT, Transformer architectures, and Retrieval-Augmented Generation (RAG) models.
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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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Job Description: The artificial intelligence platform architect will lead the development of autonomous driving software solutions with modular design and integrated platform to handle machine learning and deep learning simulation systems.
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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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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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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation.
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Ideal candidates have a strong publication record in areas including artificial intelligence data mining, machine learning, natural language processing, and/or fields such as cognitive science, learning analytics, and psychometrics.
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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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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. On any given day, you might:Evaluate open-source and internally-developed modeling and analytics tools using real business dataIntegrate internal data with external data sources and APIs to discover and implement actionable insightsDesign and craft data science models to communicate solutions to customers and company leadership We'd love to find someone who is.
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Develop next-generation technology for image processing, machine learning, and predictive analytics. Expertise in a subset of the following: machine learning, object detection, image segmentation, computer vision, image processing, remote sensing, spectral science, neural models for autonomous vehicles/robotics, structure from motion (SfM), natural language processing (NLP), large language models, data fusion, change detection, and pattern of life analysis.
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Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas. We are seeking a self-driven and highly motivated Machine Learning Engineer to join our growing machine learning teams.
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You'll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our T3 Fleet that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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Demonstrated experience in cancer genomics and omics data analyses, including experience with developing pipelines for next-generation sequencing data analysis and QC. Excellent programming skills (including R, Python, SAS) and deep-knowledge for statistical analysis and machine learning.
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