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AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Experience with open source vision and machine learning tools such as CUDA, Caffe, fastText, OpenCV, Parsey McParseface, SciKit, Torch, Tessaract, TensorFlow, Theano a plus. Intermediate or expert in one or more of image processing algorithms, machine learning, data mining, pattern matching and parallel processing using high performance computing paradigms such as GPGPU. Able to extend and improve existing algorithms to improve facial, speech, vision and gesture recognition technologies for better accuracy, robustness and ease of use.
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This role focuses on developing, deploying, and managing scalable machine learning solutions within our tech stack that includes Snowflake, dbt, Python, Kubernetes, and Java. The ideal candidate will have a strong foundation in software engineering and data infrastructure, as well as a proven ability to implement efficient, scalable, and robust decisioning platforms.
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Experience using machine learning/deep learning frameworks such as TensorFlow and/ or PyTorch. Experienced in the field of NLP/LLM and well-versed with the current and latest state-of-the-art research.
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Stay abreast of the latest academic research and open-source advancements, integrating cutting-edge technologies to continuously improve our data operations and machine learning model performance.
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By joining us as a Principal Machine Learning Engineer, Infrastructure (LLM), you will work on state-of-the-art systems, contribute to cutting-edge research, develop innovative algorithms, and play an essential part in Prescient Design's success.
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Ideally a Bachelor's degree or higher in Machine Learning, Computer Science, Computational Linguistics or other relevant technical field. deep understanding and extensive practical experience with SoTA techniques from natural language processing, machine learning, deep learning, and prompt engineering.
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2-5+ years of experience in wide range of statistical and machine-learning techniques (e.g. time series analysis, NLP, deep learning and etc.) Conduct quantitative research and predictive modeling for market related businesses by sourcing, integrating and analyzing traditional and alternative dataset to discover new insights and strategies.
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The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics to machine learning, ideally with previous experience within fraud-adjacent domains.
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This is a hands-on Machine Learning Engineer Manager so you should be someone that wants to get their hands dirty but equally someone with proven people management experience. We're searching for a hands-on Machine Learning Engineer Manager – a senior engineer with people management experience, ideally comfortable leading a growing team of 5.
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We utilize cutting-edge machine learning and contract software, enhancing traditional legal services and bringing together experts in engineering, AI, and law. Focus on continual learning and development.
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Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Our team creates world-class immersive digital experiences for the Company's premier vacation brands including Disney's Parks & Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club.
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NLP, LLM, Gen AI Model Deployment: Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability. Assist in Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions.
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machine learning jobs Title: analytics market research in New York, Fernley, Nevada
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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.
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).