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Research experience in machine learning, deep learning, and/or natural language processing. We are looking for strong research engineers who have a background in generative AI and NLP, with experience in areas like language model evaluation; data processing for pre-training and fine-tuning; responsible LLMs; LLM alignment; reinforcement learning for language model tuning; efficient training and inference; and/or multilingual and multimodal modeling.
$177,008 - $251,000 a yearFull-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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Background in Artificial Intelligence (AI), Machine Learning (ML) Natural Language Processing (NLP) Sitting at the intersection of quantitative and investment analysis, the professional will be a "hands-on" player/coach building a team of Data Scientists focused on the implementation of Data Science technologies, techniques and methodologies leveraging Artificial Intelligence (AI) and Machine Learning, advanced analytics, and statistical methods.
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Master's degree in Electrical Engineering, Computer Engineering, or related fields with courses work in Digital Signal Processing, Image Processing, Computer Vision, Data Structures, Pattern Recognition, Machine Learning.
$126,984 - $130,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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If you have industry experience developing production software for machine learning, especially in areas like recommendation engines, natural language processing, and deep learning for text data, we'd love to talk to you.
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Academic and commercial groups around the world are powering a revolution in artificial intelligence using deep learning techniques running on NVIDIA GPUs, enabling breakthroughs in problems from image classification to speech recognition to natural language processing and autonomous vehicles.
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MS in Computer Science, Information systems, or Computer engineering, Systems Engineering with relevant experience in Text Mining / Natural Language Processing (NLP) tools, Data sciences, Big Data and algorithms.
$80,000 - $100,000 a yearFull-timeExpandApply NowActive JobUpdated 29 days ago - UpvoteDownvoteShare Job
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Possess a minimum of 12 years of data mining and modeling experienceProficient in one or more of the following software platforms: Python, IBM SPSS Modeler, Natural Language Processing, Large Language Models, Generative AI Applications, and/or User Activity Monitoring applicationsAdvising stakeholders on advanced data mining and technical matters, research, and applications.
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Should be competent with at least one numerically focused programming environment such as Python or Matlab using the native linear algebra, image processing, and machine learning libraries.
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Research and Innovation: · Stay up to date with the latest advancements in the field of natural language processing and machine learning. Solid understanding of natural language processing techniques, including language modeling, text classification, sentiment analysis, and machine translation.
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You have 3+ years of experience as a Data Scientist or Machine Learning Engineer. Design, develop, and optimize machine learning models and algorithms for various applications, including computer vision, NLP, and audio/video processing.
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The Figure Eight platform transforms audio, video, text, and images into high-quality annotated data to support a variety of use cases ranging from computer vision and search relevance to data categorization and natural language processing (NLP.
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PhD with specialization in artificial intelligence, natural language processing, machine learning, or computational cognitive science 10+ years of combined academic and research experience.
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Strong understanding of machine learning, natural language processing, and deep learning. Stay informed about the latest advancements in AI, machine learning, and related technologies.
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VP, Communications Surveillance - Natural Language Processing Model Specialist. The Communications Surveillance Vice President role will report to the Lead of Transformation, Audit and Reporting within the Compliance Communications Surveillance function and will be instrumental in developing, deploying, and maintaining Natural Language Processing (NLP) and other model-based capabilities for the Communications Surveillance Program.
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machine learning natural language processing engineer data jobs Company: Veradigm
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Virtual Reality Job Interviews
With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
A Potential TikTok Ban?!
As you may already know, there has been a lot of talk lately about the possibility of a TikTok ban. While this has not yet come to fruition, it's important to consider the implications this could have for businesses and recruiters who rely on TikTok as a platform to market their brand, recruit new talent, and connect with their audience.
The Effects of Workplace Racism and Sexism
One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
When Rage Applying Strikes: How to Identify Unserious Candidates
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.
How to Increase Job Ad Exposure
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.
How to Navigate Hiring Out of State
The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).
Building a Candidate Pipeline Through Internships
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.