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Job Description Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities.
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Director - Artificial Intelligence & Machine Learning. Director - Artificial Intelligence/Machine Learning. Create and implement solutions with respect to complex problems/scientific questions on large scale data sets, especially using machine learning approaches, predictive models, and statistical analysis, especially in the area of genomics, proteomics, and imaging.
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Autonomous Sensor Deployment: Imagine sensors, positioning systems, artificial intelligence capabilities and wireless communications on active rail cars, all autonomously inspecting railways.
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Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP.
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Build well-designed, well-engineered, stable, performant mobile applications using Flutter, Kotlin, and/or Java. Guide and mentor other team members by providing oversight and direction. Preferred Qualifications Knowledge of cross-platform development frameworks, such as Flutter/Dart. Understanding of modern SRE best practices.
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Experience developing applications using Flutter. Strong experience using Kotlin and Java in building Android consumer-facing applications. Education Bachelor's degree in Computer Science, Engineering, Information Systems, or related field/work experience.
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Job Overview “We Power the Magic” That’s our motto at Disney Experiences Technology & Digital. Experience working in an Agile Team consisting of product managers, project managers, design, QA, and tech.
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Conducting cutting-edge research in the fields of artificial intelligence, machine learning, and robotics, specifically as they relate to autonomous vehicle technology. Experience in artificial intelligence fields, such as computer vision, deep learning, machine learning, planning, human machine teaming, and multi-robot systems.
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1+ years of hands-on experience in one of the following technical domains: machine learning, recommendation systems, pattern recognition, NLP, artificial intelligence, or a related technical field.
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Familiarity with the deployment of scalable machine learning models in a production environment. This role requires experience in Azure OpenAI, Large Language Models (LLMs), Python, and proficiency in developing applications using Streamlit, LangChain, Databricks, and Python frameworks such as Flask and FastAPI. The ideal candidate will be adept at building scalable machine learning models and deploying them to production environments and also being part of customer success teams.
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At Technergetics, we work with a wide variety of technologies, including mobile and web apps, Quantum computing, machine learning and artificial intelligence, AI-enabled edge devices, and many more.
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Demonstrated experience applying machine learning and deep learning algorithms to medical imaging analytics including CT, MR, and/or PET scans; experience in additional imaging domain (H&Es, IHC) a plus.
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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
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Analyze user stories, provide realistic estimations, and participate in sprint planning, scrums, demos, and retrospectives. Contribute to the entire development cycle, including technical design, development, testing, experimentation, analysis, and product launch.
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Evaluate and implement technologies incorporating machine learning, artificial intelligence, and music recognition technologies to further SME's content protection strategies. Knowledgeable about machine learning, artificial intelligence, and music recognition technologies.
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