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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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Data science, machine learning, optimization models, 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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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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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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Knowledge of AI and machine learning technologies, such as TensorFlow, Vertex AI, and AutoML.Experience with using IDE’s and experience with Python and PySpark. Leverage AI and machine learning technologies, such as TensorFlow, Vertex AI, and AutoML, to enhance data insights and drive business value.
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The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
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Business intelligence, analytics, and machine learning technologies including SAS, R, Teradata, Hadoop, data science and visualization tools. Security concepts and technologies related to authentication (MFA, risk based authentication, biometrics, SAML, OAuth, OpenID Connect), authorization, encryption, data protection, threat prevention, and S-SDLC best practices including one-time-password (OTP), SSL, PKI, DDoS remediation, anti-malware detection, and application scanning.
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Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark. Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure.
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Proven track record of strong quantitative testing and statistical analysis techniques as it pertains to OFAC sanctions and AML models, including name similarity matching, classification accuracy testing, unsupervised/supervised machine learning, neural networks, fuzzy logic matching, decision trees, etc.
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We optimize our clients' experience using unique proprietary technology coupled with robotic process automation, intuitive digital programs powered by machine learning, and enhanced by an extensive proprietary transaction data set.
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3+ years of experience with advanced analytics (predictive analysis/data mining/machine learning integration/NLP/statistical analysis/time series analytics) Vaco is looking for a Qlik Sense Analyst to join the team of a local client.
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Expertise in multiple modeling methodologies including survival analysis, transition rate modeling, time series analysis, credit scoring, Monte Carlo simulation, Artificial Intelligence/Machine Learning techniques such as neural networks and tree based algorithms etc.
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While here you will get to work with and get trained on end-to-end Workday suite, Adaptive Insights, and machine learning-based demand planning models. TCC supports a growth and learning environment.
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Machine Learning Engineering - Dallas, TX (Hybrid) Optimize machine learning algorithms and infrastructure for performance, scalability, and cost-efficiency. Deploy machine learning models into production environments, ensuring scalability, reliability, and real-time performance.
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Familiarity in using Databricks for big data processing, building machine learning models, and data analytics. We're seeking a Lead Software Engineer with a focus on Data Engineering, building, and maintaining data pipelines, building near real time operational data sources and real-time streaming data solutions to enhance our customer facing products while enabling predictive Machine Learning and AI solutions.
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machine learning jobs Title: expert Company: Expert Hiring in Irving, TX
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