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Collaborate with data scientists and engineers to design, build, and maintain Azure-based MLOps pipelines for automating machine learning model deployment, monitoring, and maintenance. Implement Azure-based deployment pipelines for deploying machine learning models into production environments.
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The Role As a Machine Learning Engineer you will research, develop, and support the machine learning models that allow our devices to decode evidence like a detective and define how non-violent crime is eliminated.
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Distinct experience in advanced probability, statistics, machine learning, big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP. This role involves developing data science 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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Over 8 years of experience in machine learning, predictive modeling, statistics, computer science, bioinformatics, or computational biology, specializing in neuropsychiatric disorders. The goal is to drive breakthroughs in machine learning and AI for target identification, biomarker discovery, and the advancement of diagnostics and drug therapies in brain health.
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Collaborate with data scientists, software engineers, domain experts, and client stakeholders to understand requirements, gather feedback, and integrate machine learning solutions into larger systems or products.
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Experience using cloud computing for machine learning and deep-learning frameworks such as TensorFlow, PyTorch, Keras. Publication record in NLP, Machine Learning, Computer Vision or related areas preferred.
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Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in Springfield, VA or St. Louis, MO. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. As a Machine Learning Engineer you will help ensure today is safe and tomorrow is smarter.
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Build collaborative relationships with key stakeholders; set priorities aligned to business goals; communicate analysis, strategies, timelines, and work of the data science & machine learning team, and gain buy-in from executive leadership.
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Design, develop, and implement machine learning models and algorithms to solve complex problems across various domains, including but not limited to recommendation systems, natural language processing, and predictive analytics.
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You will develop robust and scalable data pipelines, ML model hosting, and backend services for enterprise line of business applications in Python, VertexAI, Airflow, dbt, Flask, PostgreSQL, BigQuery, Docker, Kubernetes, and more.
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Develop business models and high-quality prediction systems, leveraging machine learning algorithms and artificial intelligence tools to prioritize various improvement models for implementation.
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API Development & Deployment: Develop and implement APIs using Flask, FastAPI to deploy machine learning models and integrate them into existing systems or applications. Five or more years of industry experience in data science with a focus on data analytics, machine learning, and deep learning.
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AI and Machine Learning, Azure Blobs, Office 365, Dynamic 365, Logic apps, Power apps, MS Flow, Power BI, Sharepoint o GitHub DevOps, CI/CD, workflows, actions and Ansible automations Skills Required : o Cloud solutions, design, architecture and security o Evaluating hardware.
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With tech innovation an integral part of our core business, the booming city proved an ideal backdrop for our heavy investment into machine learning, research infrastructure and big data computing.
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business systems machine learning jobs Title: intelligence Company: Amazon Jobs
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