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The Senior Machine Learning Engineer will serve as a key technical leader, driving the design, development, and deployment of advanced machine learning applications. Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.
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Architect OpenVPX DSP systems using Annapolis Micro Systems products for applications such as Electronic Warfare (EW), Signals Intelligence (SIGINT), Synthetic Aperture Radar (SAR), Software Defined Radio (SDR), Artificial Intelligence (AI), Machine Learning (ML), and Digital Beamforming (DBF.
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Domain expertise: programming languages, data analytics, machine learning (ML/AI), DevSecOps, Cloud, Big Data. Software/Tools: AWS, Docker, Jira, VMware vCenter/vRealize, Kubernetes, Jenkins, Ansible, Prometheus, and Grafana; Cloud Native: AWS EC2, AWS CDK, S3, CloudWatch, CloudFront, CloudConfig, Elastic Container Services (ECS), DynamoDB, RDS, ElasticSearch, PowerBI, Tableau.
$110,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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For this Senior Data Scientist role, we're looking for someone with data science and machine learning experience who likes the challenge of breaking new ground. 2 years of AIOps experience - Automating (MLP, Deep Learning, or LLM Models) via cloud data engineering pipelines within Azure Synapse and Databricks.
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Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Project Management, Software Development, Stakeholder Relationship Management.
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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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We specialize in Computer Network Operations (CNO), embedded development, software engineering, cloud engineering, Artificial Intelligence and Machine Learning (AI/ML), DevOps support, systems engineering and more.
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As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. We are looking for a motivated and self organized Machine Learning Engineer who can build and deliver state of the art batch, streaming and real time ML and AI solutions to join the Marketing program to drive powerful experiences for our users.
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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Requires a Bachelor's degree in Cognitive Science, HCI, Psychology, Sociology, Anthropology, Information Science, Economics, Political Science, Mathematics, or related field and one year of work experience in job offered or in a user experience/research or computer-related occupation.
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Ensure steady process of transfer of advanced technology research (GenAI, LLM & SLM, machine learning, text & data mining) into core product development roadmaps. Product Management Director – OVID Health Technology (M.D.
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We are seeking an experienced Machine Learning Engineer or Data Scientist with technical expertise in Recommender Systems, Natural Language Processing (NLP), and Computer Vision, to join our growing team of multidisciplinary data science and ML experts.
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Applications: Elasticsearch with Machine Learning, Mattermost, Custom Authentication code, NGINX, Prometheus, Graphana, Kibana, pwick, TerraForm, Ansible and Docker. GliaCell's Enterprise capabilities include Full-Stack Application Development, Big Data, Cloud Technologies, Analytics, Machine Learning, AI, and DevOps Containerization.
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Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
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Experience with Machine Learning and related technologies such as Tensorflow Python, Torch, Amazon SageMaker, Jupiter Notebooks, git. Possess deep functional and technical understanding of the Machine Learning technologies (Googles Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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