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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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You have successfully led one or more of the following Finance projects: process automation or standardization, operating model, process reinvention using RPA, Applied Intelligence, Machine Learning, or GenAI.
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Draw on experience with Github, machine learning, advanced programming in SQL and Python, Cloud computing such as AWS, Google and Azure, Tableau, and Simio to design, develop and implement a broad array of business analytics that solve complex problems in a computationally efficient manner by leveraging advanced understanding of statistics and data science.
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A little about ADP: We are a global leader in HR technology, offering the latest AI and machine learning-enhanced payroll, tax, HR, benefits, and much more. ADP is hiring a DLP Engineer, focused on EMail and/or Network DLP.
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Experience in analysis, data analysis, data visualization, mathematics, statistical data mining, or data science. Experience in business analysis, data analysis, mathematics, data warehousing, statistical data mining, and/or data science.
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Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning, data visualization and other quantitative methods.
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Admission and Recruitment Marketing, the Generalist/Data Processing Clerk works as part of a team to. The Generalist/Data Processing Clerk will handle general. the Generalist/Data Processing Clerk will.
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As a Site Civil Engineer / Landscape Architect, you will develop work within the different facets of civil engineering related to the Renewable Energy industry and collaborate with an outstanding team of technical professionals across disciplines.
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He/ She will work as a Senior Cloud Engineer within the CDO EDP team and will have the opportunity to work one-on-one with application and infrastructure developers to build and enhance the data infrastructure and application patterns that power mission-critical applications, ensuring that they are engineered for high availability, durability, and resiliency.
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We are looking for a BC/BE Physiatrist/PM&R Physician to join our Physiatry run team in Northern NJ. Our physicians work in post-acute care settings providing consultation and follow-up care. Board Certified or Board Eligible in PM&R.
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Digital transformation is everywhere, with technologies such as Multi-Cloud, Cybersecurity, Automation, IoT, AI, Machine Learning, and 5G driving the next waves of innovation. This role is for a Consulting level , Pre-Sales Engineer that will have broad SP knowledge and responsibility for a single top tier US Service Provider , AT&T , preferably based in the Middletown, NJ area.
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Experience with MasterCard, Visa, Discover, American Express and Diner's International merchant acquiring; settlement balancing and error processing. Experience in merchant acquiring system and credit & debit card international processing & integration services.
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Solid knowledge of scripting languages such as shell scripting, JavaScript, web programming like HTML and JSP, Python, Ansible, SQL stored procedures for MS SQL Server and workflow development. Job Title: MFT Engineer.
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Summary / Job Objective: As a data engineer/developer, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that are used for collecting, storing, processing, and analyzing large volumes of data.
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