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As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Advanced Degree: Master's or PhD in Computer Science, AI, Linguistics, or related fields, with a focus on machine learning and natural language processing. In your role as a Senior Machine Learning Engineer, you will focus on leveraging and optimizing Large Language Models (LLMs) along with the implementation of advanced AI technologies.
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Experience in machine learning, deep learning, information retrieval, knowledge graphs, natural language processing or data mining. MS or PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Machine Learning, Information Retrieval, Data Science or related field.
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Leveraging computer vision, natural language processing, machine learning, and vertical-specific large language models (LLMs), Lily AI enhances customer shopping experiences by injecting consumer-centric language throughout the retail technology ecosystem.
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Experience in machine learning, deep learning/LLM, information retrieval, natural language processing. The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing.
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3 years of experience with machine learning algorithms and tools (e.g., TensorFlow), or applied ML (e.g., deep learning, natural language processing). We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day.
$189,000 - $284,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Required Technical Skills: Deep knowledge of AI principles, including natural language processing (NLP), computer vision, and reinforcement learning. We offer a unique and immersive online learning platform, powering corporate technical training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more.
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Strong deep learning, particularly in applications of Neural Network architectures to Computer Vision, Natural Language Processing, Machine Intelligence and/or Reinforcement Learning.
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Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in problems from LLM, image classification to speech recognition to natural language processing.
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Ph. D. degree in Artificial Intelligence, Machine Learning, Robotics, Computational Neuroscience or related technical field with a strong publication/practical implementation or any field.
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Research focus on one of the following: Computer Vision, Deep Reinforcement Learning, NLP, ASR, Audio Processing. HP Labs Senior Machine Learning Research Scientist. Interest in controlling physical systems using Machine Learning.
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Apple Silicon Engineering is seeking Hardware-minded Software engineers to build innovative tools to design the next generation of Apples world-leading systems-on-chip (SOCs) Apples 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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Image Processing, Computational Imaging, Computer Vision; Practical experience with Deep Learning, Machine Learning, or Artificial Intelligence, for images, is preferred; Capable of prototyping Algorithms using MATLAB or Python, and implementing algorithms in C.
$87,400 - $148,600 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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MBRDNA is headquartered in Silicon Valley, California, with key areas of Autonomous Driving, Advanced Interaction Design, Digital User Experience, Machine Learning, Customer Research, and Open Innovation.
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As an engineer on this team you will have the opportunity to - build enterprise products that solves real world problems by leveraging our machine learning platform, build the foundational frameworks and services which abstracts away the product needs and provides scalable and reliable building blocks, build the enterprise data platform for various product needs.
$130,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago
machine learning natural language processing next generation jobs Title: engineer in Sunnyvale, CA
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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.
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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.
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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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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.