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Applied AI ML opportunities are available at the VP level for our Quant AI team within the Machine Learning Center of Excellence. Deep knowledge in Machine Learning, Deep Learning, Data Mining, Information Retrieval, Statistics.
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Expected familiarity with applied machine learning techniques and numerous machine learning algorithms, including classification and regression algorithms, market basket analysis, etc.
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Within Bloomberg Law (BLAW), the BLAW Machine Learning Team is the central machine learning engineering team with 10 machine learning engineers working with groundbreaking technologies to build data-driven customer-facing products using Natural language processing (NLP), Information extraction (IE) and Machine Learning (ML) techniques such as named entity disambiguation, text classification, clustering and topical modeling, text summarization and personalized recommendations.
$165,000 - $260,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Committees may include topics such as AI/machine learning, ethics, natural language processing, data definitions, data governance, genomic/pathology/radiology and other specialized clinical data systems, Epic, internal and external data reuse, learning health systems and translational science.
$183,854 - $289,990 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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KEYWORDS Machine Learning | Physics | Embedded Systems | Signal Processing | Data Analysis | Nvidia | Electrical Engineering | Cloud Computing | Cuda | TensorRT | Radio Frequency | Transmission Processing | Linux OS | Pytorch | Python | Edge Computing.
$80 - $90 an hourExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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PhD in one of the following fields: deep learning, artificial intelligence, machine learning, computer science, robotics, computer vision, computational neuroscience, signal processing, speech and language technologies, or related fields.
$143,000 - $208,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Lead the technical trajectory of a team utilizing deep learning and LLM-based NLP models. As a Staff Machine Learning Engineering Manager, you will work with cross-functional leads to design solutions in a highly ambiguous, impactful, and interesting problem space with a high degree of autonomy.
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You have successfully led one or more of the following Finance projects: process automation or standardization, operating model, process reinvention using RPA, Applied Intelligence, Machine Learning, or GenAI.
$131,100 - $336,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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AI, Machine Learning, Deep Learning. Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
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Expertise with CI/CD processes and contributes to a sustainable and robust codebaseExperience with batch jobs/data pipelines and is comfortable deploying through these systems (i.e. Airflow, Luigi, Composer)Build and interact with production systems for serving machine learning predictions.
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Experience with data science / machine learning algorithms and tools (R, Python, or other development tools) required. Independently conducts advanced, complex analyses of internal and external client or industry data sources and leads the development of statistical models and/or machine learning algorithms for analyzing and predicting client behavior, securities performance, risk or economic data.
$108,700 - $175,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Explore complex challenges and transform how the bank operates with Applied AI ML opportunities at Sr. Associate, Vice President, and Executive Director level in New York, Palo Alto, and Seattle, WA. As a Machine Learning Scientist, you'll apply sophisticated methods to tasks like natural language processing, speech analytics, and recommendation systems.
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If your background is in Computer Science and Engineering, Data Analytics, Statistics, Biostatistics, Mathematics, Operations Research, Machine Learning, Management Information Systems, or Security Information Systems , learn more about CRA.
$87,000 - $91,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Databricks for data engineering, analytics, and machine learning. Utilize Databricks for data engineering, analytics, and machine learning tasks. The ideal candidate will possess a deep understanding of database design principles, SQL Server administration, Azure cloud services, Databricks, and Python programming.
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4+ years of professional experience in environmental consulting / Energy market with applied science and permitting in the fiber optic siting/permitting sector and associated marine environment impact assessment skills to assist in support in the OSW (Offshore Wind) market to include studies, surveys and permitting in support of BOEM, SAP and COP Submittals.
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machine learning deep applied science jobs Company: Amazon in New York, Bentonville, Kansas
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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.
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.