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Programs on 5G, quantum computing, artificial intelligence, deep learning, quantum computing and from artificial intelligence and deep learning to cyber. programs on 5G, quantum computing, artificial intelligence, deep learning.
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Hands-on experience with signal processing, data analysis, machine learning models, or platform development in radar, lidar or equivalent. Prior research experience to one or more of the following areas: Electromagnetics and antenna technology (simulation tools such as CST and HFSS, characterization techniques) Radio-frequency systems (wireless communication, radars, SDRs) Signal processing and machine learning (DSP, wireless perception algorithms.
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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.
$132,000 - $264,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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As a Google Vertex Full Stack Software Engineer, you will be responsible for developing and implementing machine learning models using Google Vertex AI and developing consumable API microservices using Typescript, Node.js, Express.
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As a machine learning engineer, you’ll have the opportunity to immediately drive a huge, direct impact for Propel! Lead Propel in building machine learning infrastructure that all teams can take advantage of.
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Have expertise in Machine Learning best practices (e.g. model evaluation and hyperparameter tuning, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection.
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We are seeking a highly motivated machine learning and AI Principal Scientist to join our Computational Tissue Imaging Research team in the Translational Bioinformatics organization.
Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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You'll code with machine learning languages like DataBricks and Python Libraries to synthesize millions of data sets into patterns that answer ad hoc requests and then use Tableau for data visualization.
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Utilize expertise in models that leverage the newest data sources, technologies, and tools, such as machine learning, Python, Hadoop, AWS, as well as other cutting-edge tools and applications for Machine Learning.
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Develop and implement train machine learning models using Google Vertex AI and Typescript, Express. Design, build, deploy machine learning models and microservices on the Google Cloud Platform.
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Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
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5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.
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Optimize and fine-tune machine learning models for performance and efficiency. 1 + years of experience in machine learning engineering or a related field. Stay updated on the latest advancements in machine learning and AI technologies.
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2 + years of experience working with SQL, NoSQL databases, and big data platforms. Familiarity with Front-end web development technologies (React, Vue.js, Angular, etc.) 2 + years of experience with developing microservices and implementing CI/CD pipelines via cloud computing services like (Google Cloud Platform preferred), AWS, Azure or similar.
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4+ years of experience implementing and applying algorithms for machine learning and artificial intelligence. Proficiency with standard machine learning tools and frameworks: Python, PyTorch, Huggingface Transformers.
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machine learning jobs Title: data scientist Company: Verizon
FEATURED BLOG POSTS
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.
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.