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LLM, NLP, DL (Deep Learning), Client (Machine Learning), object detection/classification, tracking, etc. · Stay up to date with the latest advancements in LLM, NLP, deep learning, machine learning, and object detection algorithms, and proactively identify opportunities to leverage new technologies for improved solutions.
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Our earliest products power federated machine learning missions for clients in several industries, where data privacy, low latency serving, and low cost of data storage are important to the client.
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I have been working at Nutanix since May 2021, primarily on the machine learning algorithm side but also in areas like MLOPs lifecycle management, data preparation, and deployment.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$143,000 - $286,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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We are looking for a highly skilled and experienced Sr Machine Learning and Generative AI engineer who has a robust understanding of Large Language Models and Generative AI to help work on exciting technologies for future Apple products and bring it to live.
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Adobe Firefly Applied Science & Machine Learning (ASML) group is looking for an Engineering Manager working on generative AI models for image synthesis to help us build the next generation of creative tools.
$148,600 - $298,800 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - 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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You will drive the technical, product, marketing and go-to-market engagement with strategic partners, play a significant role in identifying product gaps and defining future features for NVIDIA's products, and advocate partners’ success with NVIDIA. An ideal candidate has expertise in Physics Informed Machine Learning, a proven technical background in Deep Learning, and experience of ecosystem development.
$180,000 - $339,250 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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You will learn practical modeling skills, as well as software skills to be a successful machine learning engineer. You will identify an applied machine learning problem in the enterprise search and question answering ecosystem.
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Job Description Summary: We are seeking a talented and driven AI Machine Learning Scientist to join PayPal’s nascent Strategic Generative AI Unit. The Strategic Gen AI unit’s charter is to orchestrate and facilitate adoption of Gen AI techniques and algorithms across enterprise business use cases by providing technical consulting as well as conducting applied R&D to explore building in house generative AI capabilities.
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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.
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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). Understanding of advanced Machine Learning development, with the ability to work full-stack from API design to programming languages, runtimes, compilers, and advanced hardware.
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As a research scientist at Adobe, you will be joining a dynamic team of machine learning, deep learning, natural language processing, and computer systems researchers to build the future of digital experiences.
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NVIDIA is seeking architects like you to help design hardware accelerator and processor architectures that enable state of the art machine learning and data analytics algorithms and applications on our next-generation mobile, embedded and datacenter platforms.
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Technical and/or legal background in software, artificial intelligence/machine learning, email security and/or cloud security. Analyze new threats and offer deep insight through data-driven intel.
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machine learning jobs Title: sr data scientist Company: Apple in Santa Clara, CA
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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.
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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.
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.