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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
$220,000 - $275,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Solid ML background and familiar with standard NLU, NLG, and LLM techniquesPREFERRED QUALIFICATIONS- PhD in Computer Sciences, Electrical Engineering, or Mathematics with specialization in machine learning, deep learning, or natural language processing- 4+ years experience in building conversational AI and/or natural language processing systems.
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We process billions of mail messages using cutting edge algorithms in areas including but are not limited to: Natural language processing, GenAI, Large Language Models, Machine Learning techniques, big data processing in order of petabytes to: Extract information, build mail content and user knowledge, and interconnect different sources to identify, highlight and amplify what matters.
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Overview Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs.
$130,000 - $170,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep understanding of deep learning architecture, machine learning, natural language processing (NLP), and generative models. Design and develop solutions that utilize generative AI, leveraging Machine Learning (ML) and Large Language Models (LLM), tailored to business needs.
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Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, and/or Reinforcement Learning. Stay informed and integrate latest statistical modelling, machine learning, deep learning, recommender system and/or artificial intelligence trends to improve and enhance modelling stack and improve business metrics and customer experience.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Ideal candidates have a strong publication record in areas including artificial intelligence data mining, machine learning, natural language processing, and/or fields such as cognitive science, learning analytics, and psychometrics.
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Experience with natural language processing (NLP) and deep learning frameworks TensorFlow, PyTorch). Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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The Opportunity 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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Programming: You are proficient in Python or other high level programming language with experience in using geospatial and machine learning libraries (eg., OpenCV, TensorFlow, PyTorch etc.
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Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Deep knowledge and experience of managing, orchestrating, and monitoring distributed production systems.
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Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
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10+ years of experience in natural language processing, machine learning, or a related field. - Gain deep understanding of driver needs, Amazon Flex and SDS business and operations strategy, and the WWCS and Last Mile technology landscapes to align most impactful opportunity for large language model (LLM) empowered product features.
$196,900 - $340,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are doing the world-class work in machine learning, computer vision, natural language processing, speech and audio, knowledge and data mining, and transferring our work into ByteDance which are used by hundreds of millions of users around the world.
$129,960 - $194,750 a yearFull-timeExpandApply NowActive JobUpdated Today
machine learning natural language processing deep engineer jobs Company: Intuit
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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.
Recruitment strategies that are weird, but actually work
In the current candidate-driven job market, recruiters are looking for unique ways to attract talent. Some have resorted to even (dare we say it?) recruitment strategies on the border of weird and wacky. What can we learn from the unusual recruitment tactics that are being used and actually getting results? Here’s a rundown of some unique recruitment strategies that actually work.
How To Make $100K a Year – No BS Strategies & Advice
If you’re like most of us, you’d love to be wealthier. Having more money would alleviate stress. It would make it easier to pay your bills and buy nicer things. Maybe it’d allow you to spend more time with your kids and go on more vacations. You’re not alone if you wish you could somehow earn a more significant income.