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This role is part of the team focused on deploying new and emerging capabilities to out our next generation cloud-based HR, Payroll, analytics, and machine learning platform.
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4-7 years Oracle SOA / Service Bus / Oracle Integration Cloud Req. Experience with developing and Maintaining Integrations with Oracle SOA suite and Oracle service bus.
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Shape the future with next-generation AI: Join us as a Machine Learning Engineer! Deep Learning Ninja: Proven experience in designing and implementing machine learning solutions utilizing GCP and various algorithms (e.g., TensorFlow, PyTorch.
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Net, C#, Android SDK, Kotlin, IOS Swift, AWS: EMR, S3, Redshift, Athena, Glue, DynamoDB, Lamda, CloudWatch, ElastiCache, Kinesis, SNS, SQS, Azure: HDInsight, Data Factory, Data Lake Analytics, Databricks, GCP, and Big Data Apache: Hadoop, Hive, Hue, Sqoop, Kafka, Spark, Airflow, SnowFlake, Python, Scala, Machine Learning: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Apache Mahout, Vertex AI, Keras, OpenNN, Theano.
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Our next-generation platform, which combines threat intelligence with machine learning, enables financial institutions and governments to detect cryptocurrency fraud and financial crime at an unprecedented scale.
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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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As a Research Engineer working at the Reality Labs, you will be responsible for the implementation and acceleration of our EMG machine learning platform; creating new AI models, tools, and infrastructure that unlock the capabilities of our technology; productionizing our research results, and working with scientists, software engineers, hardware engineers and designers to advance the company's AI-driven AR/VR agenda.
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Customer Systems Team is developing next generation AI and engineering solutions to optimize and enhance the support experience for Apple Care support customers. We are looking for a hands-on machine learning engineer who is passionate about crafting, developing, and deploying cutting edge AI/ML solutions which will impact millions of customers.
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Conducts advanced analytics leveraging predictive modeling, machine learning, simulation, optimization and other techniques. Master s degree with coursework in advanced Machine Learning techniques (Natural Language Processing, Deep Neural Networks, etc.
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2 to 5 years of experience using Oracle Integration Cloud (OIC) and/or Oracle SOA Suite. Additional preference for Oracle certifications in any of the following cloud products: Benefits, Compensation, Payroll, Absence Management, Talent Management, Learning or Recruiting Cloud.
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You will be responsible for designing, developing, and integrating core applications for CAD geometry preprocessing, including feature detection, slicing, layer generation, tile position generation, tile sequencing, engineering analysis, print process simulation, support generation, optimization and generative design for area printing, and machine learning / AI integration.
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As a Machine Learning Engineer at Nelnet, you'll be at the intersection of data science and software engineering. Our Machine Learning Engineer role is at the core of this transformation, creating intelligent systems that automate processes, derive insights, and enable us to make better decisions.
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The team uses emerging technologies and methods such as data fabric, machine learning, GenAI, NLP, computer vision, artificial intelligence automation, big data analytics, and cloud native application development to drive innovation, operational efficiency, and provide the data product excellence our customers have come to value and trust us for.
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Apple Silicon Engineering is seeking Hardware-minded Software engineers to build innovative tools to design the next generation of Apple's world-leading systems-on-chip (SOCs) Apple's multi-billion-transistor Ax SOCs are the brain of every iPhone and iPad. The Analog Mixed-Signal (AMS) circuits connect them to the physical world via complex IPs such as SERDES for data communication, PLLs for clock generation, and sensors for measuring physical quantities.
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Collaborate closely with product teams, business stakeholders, MLOps, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
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