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Deep Learning Ninja: Proven experience in designing and implementing machine learning solutions utilizing GCP and various algorithms (e.g., TensorFlow, PyTorch). As a Machine Learning Engineer specializing in Google Cloud Platform (GCP), youll lead the charge in developing and deploying cutting-edge solutions that extract valuable insights and drive tangible business outcomes.
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Data Scientists on Riot Esports teams are responsible for feature development in support of Esports live broadcast outcomes, notably defining the algorithms and models used to generate match statistics during broadcasts, and for using statistical analysis and machine learning methods to support the development of narrative and analytical segments for live Esports broadcasts.
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Databricks Certifications (ie: Data Engineer Associate; Data Engineer Professional, Machine Learning Associate, Machine Learning Professional) Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, GCP, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
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Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
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When performing any tasks involving hazardous chemicals or hazardous waste, the Processing Technician II will follow the regulations and requirements of SPCC Plan, RCRA regulations and operating procedures involving hazardous chemicals outlined in the Huck Fasteners Environmental management.
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Demonstrated ability and clear plans for teaching and curriculum in either areas of Data Science, Artificial Intelligence, Natural Language Processing, Computer Vision, Computer Security, or Software Engineering, or related fields.
$5,405 - $11,994 a monthFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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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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Natural Language Processing (NLP): To understand the context and sentiment behind content engagement and social media interactions. NLP libraries such as NLTK or SpaCy for processing text data.
$100,000 - $140,000 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Hands on experience with Modern Data Warehousing in cloud, Azure Data Factory, Azure Databricks, Pyspark, Azure DevOps, Azure Machine Learning, Azure Data Lake, Power BI, MS SQL Server, SSAS, SSRS, SSIS, Tableau, Alteryx, Natural Language Processing, Scikit-Learn (Classification, Clustering and recommendation system.
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Ring Data Management is seeking a self-directed System Development Engineer to develop and operate our AWS cloud data processing systems. - 3+ years of experience with a modern scripting language such as Python, TypeScript, or Ruby.
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Performs basic trial runs to check accuracy of machine settings or programmed control data. Technical Skills - Understands and has working knowledge of the manufacturing production control and use of machinery operation process, procedures and function; use and understand basic computer entry and processing skills.
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Position Overview We are on the lookout for an enthusiastic Volunteer Natural Language Processing (NLP) Specialist to join our innovative team. We are excited to see how your expertise in Natural Language Processing can help shape the future of our foundation.
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Proficiency in programming languages such as R, Python, and SQL, with experience in data analysis and machine learning tools like PyTorch, Pandas, scikit-learn, Tensorflow, or similar. Minimum Experience: 2 years of industry experience in dedicated machine learning or data engineering roles, or equivalent to a Master’s degree with strong emphasis in Machine learning.
$115,830 - $129,279 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Manage services from Public Cloud Hyperscalers like Microsoft Azure, Amazon AWS, Oracle OCI, Google GCP, and Alibaba Cloud on services like Cloud Compute, Storage Services, Data Services, DevOps, CI/CD, MicroServices, Service Mesh, Containerization, Artificial Intelligence, Machine Learning platforms and End-to-End Observability.
$185,000 - $205,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Have some experience in multiple modalities of deep learning, such as computer vision, natural language processing or audio. Strong technical background in machine learning and deep learning.
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As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
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In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
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Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
Hiring Transparency
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