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Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Expertise in data strategy, data architecture, data engineering, advanced analytics, data science, data mining, and machine learning. Has experience managing on-shore and off-shore teams and knows how to optimize operating models to ensure data entry, data operations, and data thought leadership is being performed by the right talent base with scale and speed.
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We work alongside product teams across MI ES on break-through ideas using tools and techniques spanning the entire spectrum of Data Science, Statistics, Machine Learning, Deep Learning, NLP, Gen AI, Operations Research, Data and Machine Learning Engineering.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Drive both short term and long-term research initiatives in areas such as artificial intelligence, machine learning & data mining, natural language processing, bigdata systems, information and data visualization, social & cognitive science.
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The Research Associate Data Scientist participates in biomedical research projects using programming, data mining, statistics, machine -learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis.
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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer Sunnyvale, California, United States. The Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipelines based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle issues or provide recommendations for the next step of solving problems.
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To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. The FBA team is looking for a passionate, curious, and creative Principal Research Scientist with expertise in operations research, machine learning or statistics, along with a proven record of solving business problems through scalable modeling and analytical skills.
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Deep knowledge in statistics and Machine Learning models, deep learning models, NLP, Generative Adversarial Networks (GAN), and other generative models. Experience working on all aspects of enterprise scale implementation for AI/GenAI solutions including architecture, design, security, infrastructure, MLOps/GenAIOps Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn.
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Experience in assessing and implementing new data tools to enhance the machine learning stack. We are a growing subsidiary of a large public company that is hiring a talented Lead ML Engineer / Senior Machine Learning Engineer.
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Lead large transformations for former employers and has evolved & matured current Master Data Management, Data Governance, Data Architecture, Data Quality, Enterprise Data Management, and Data Design practices.
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100% REMOTE Senior ML Ops Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company! Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, PyTorch, Tensorflow/Keras, MLlib, etc.
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Our client in Forth Worth, Texas is looking for an FEA Engineer with Artificial Intelligence and/or Machine Learning experience. Possess a sound grasp and at least one year experience in applying AI/ML, surrogate modeling, and deep learning techniques.
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Apply your expertise in machine learning, data mining, and information retrieval to design, prototype, and build next-generation analytics engines and services. We are a well established Defense contractor with deep expertise in Machine Learning and Deep Learning projects for Military and Homeland Security programs.
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machine learning data mining deep jobs Title: research scientist Company: Fluence Corporation
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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.
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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?
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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.
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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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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.