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Key word search: Python, Master's degree, predictive maintenance, preventative maintenance, relocation package, data science. Work with plant engineers located globally to solve business challenges related to forecasting the breakdown of the machines using sensor data analysis techniques such as Vibration Analysis, Motor Circuit Analysis, Oil Analysis, and Infrared Thermography.
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Working knowledge in one of the following areas: machine learning, deep learning, backend, large-scale systems, data science, full-stack Experience with Big Data Frameworks, such as hadoop, spark, flink, etc.
$145,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure. Prior experience building machine learning systems in production such as enabling data analytics at scale.
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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.
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Applies advanced data science, machine learning, and deep learning algorithms necessary to derive insights and develop solutions on enterprise-scale providing a competitive advantage.
$92,300 - $175,400 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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This position gains experience in various areas including, but not limited to: predictive modeling; personalization and recommendation algorithms; search recall, precision, ranking, and related problems; sensor fusion models, optimization and mathematical programming with applications in labor scheduling, capacity planning, and inventory optimization.
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Experience with distributed large-scale data processing (preferably Apache Spark). As a Senior Software Engineer in the Central AI team, you will build and maintain the core infrastructure to allow machine learning engineers and data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines.
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Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python). Expert-level with search platform, deep learning training/inference platfrom. Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking.
$206,300 - $305,700 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are revolutionizing how shows, movies, and games are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving the discovery and personalization of our offerings to our global user base using Machine Learning and data analytics.
$100,000 - $720,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience in building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search, etc. Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing.
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Experience in building large-scale machine learning infrastructure for online recommendation, ads ranking, personalization, search, NLP, etc. Preferred to have knowledge of machine learning, data mining, information retrieval, statistics or natural language processing.
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Whether you join our Statistics, Optimization, or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Search and Personalization rely.
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Experience in one or more of the following areas: NLP, Ranking, Ads, search engine, recommender system, distributed system, and machine learning. Responsible for the research and application of the company's large-scale models, exploring new applications and solutions for related technologies in the fields of search, recommendation, advertising, content creation, and customer service, to meet the growing demand for intelligent interactions from users and comprehensively improve their way of life and communication in the future world.
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Expertise in natural language processing, search and recommendation, and machine learning with a passion for data-centric machine learning. Ph. D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics, related field; or equivalent experience.
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Whether you join our Statistics, Optimization, or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithmsthat power solutions our partners in Marketing, Supply Chain Optimization, Search and Personalization rely on.
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FEATURED BLOG POSTS
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).