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Deep understanding of deep learning architecture, machine learning, natural language processing (NLP), and generative models. Design and develop solutions that utilize generative AI, leveraging Machine Learning (ML) and Large Language Models (LLM), tailored to business needs.
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Knowledge and experience developing and applying algorithms in one or more of the following machine learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods.
$159,324 - $245,544 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Overview Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs.
$130,000 - $170,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Stay informed and integrate latest statistical modelling, machine learning, deep learning, recommender system and/or artificial intelligence trends to improve and enhance modelling stack and improve business metrics and customer experience.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Job Description: The artificial intelligence platform architect will lead the development of autonomous driving software solutions with modular design and integrated platform to handle machine learning and deep learning simulation systems.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. Difference between Machine learning, Artificial Intelligence and Deep learning.
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Deep Learning and Computer vision. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Recognizes the companies of ADUSA as our customers and actively looks for opportunities to improve service and performance through enhanced use of LMS. Has a deep knowledge of the business needs and software applications to provide value-added solutions and facilitate the Learning Administration team’s strategic and functional activities by developing project initiative proposals, organizing project teams, reviewing team performance to achieve project deliverables and milestones.
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Proven experience with antimicrobial peptide design, including deep learning models. Utilize expertise in computational biology, machine learning, and bioinformatics to develop and optimize algorithms and models for the analysis of high-dimensional biological data.
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We are looking to add an experienced Machine Learning Engineer to our esteemed team who can develop cutting edge Deep Learning technologies in the domains of Computer Vision, Synthetic Aperture Radar (SAR), and Geospatial Exploitation.
$120,000 - $190,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Technical Skills or Knowledge:Experience with one or more machine learning and deep learning frameworks such as TensorFlow, PyTorch, or Keras. The Research Computing Center (RCC) seeks to hire an experienced Computational Scientist – Scientific–AI and Machine Learning to serve as a domain expert in supporting and advising faculty, post-docs, and graduate students on projects in a wide range of research domains.
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Experience with natural language processing (NLP) and deep learning frameworks TensorFlow, PyTorch). Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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Qualifications Minimum Qualifications On going MS or Ph. D student in Visual Computing, Computer Vision, Computer Graphics, 3D Vision, or related field industry or research experience with deep learning and computer vision Experience with Python Familiar with linear algebra, and numerical optimization Experience with cloud platforms such as GCP, Azure, or AWS Experience with machine learning and deep learning and modern 2D and 3D Vision.
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Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for deep learning development and deployment. Requirements Key Responsibilities: Model Development: Design, implement, and optimize deep learning models for a wide range of applications, including image recognition, natural language processing, and autonomous systems.
$150,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated Today
deep learning jobs Company: Cvs Health
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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
Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
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If you’re like most of us, you’d love to be wealthier. Having more money would alleviate stress. It would make it easier to pay your bills and buy nicer things. Maybe it’d allow you to spend more time with your kids and go on more vacations. You’re not alone if you wish you could somehow earn a more significant income.