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Extensive knowledge in machine learning and hands-on experience in developing and implementing deep learning algorithms and generative models like VAEs, GANs, autoregressive models and transformers.
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Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, Ads Data Hub, BIQuery, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK.
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Knowledge of software and algorithm development, machine-learning algorithm development, or artificial intelligence techniques applied to digital RF signal processing, RF engineering or spectrum theory, communication systems, electronic warfare, SIGINT processing, or related areas.
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The ideal candidate is an experienced software developer with a focus on machine learning, ideally familiar with GCP and Vertex AI. This Sr Machine Learning Python Developer role will involve supporting the AI model development process in our AI Pillar.
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This will be a hands-on / applied machine learning role with a focus on Generative AI, RAG, and document understanding (Taxonomy, Digitization, Classification, Extraction, Validation, etc.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Bachelor’s Degree required from an accredited, not for profit university or college, with degree preferably in Computer Science, Data Science, Statistics, Machine Learning, or Mathematics.
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23andMe is seeking exceptional researchers with backgrounds in machine learning, statistics, physics, applied mathematics, and/or computational biology. Deep understanding of computational biology, statistical genetics, and/or machine learning.
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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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Bachelor's, Masters, or PhD degree preferred in Machine Learning, Robotics, Computer Science, Computer Engineering, Mechanical Engineering, Applied Mathematics, Statistics, or a related field.
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Analyze specifications, lays out metal stock, sets up and operates machine tools, and fits and assemble parts to make and repair metalworking dies, cutting tools, jigs and fixtures, gauges, and machinists' hand tools, applying knowledge of tool and die designs and construction; shop mathematics; metal properties; and layout, machining, and assembly procedures.
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We are seeking a highly motivated Machine Learning Engineer Co-Op from July 2024 to December 2024, focusing on Natural Language Processing (NLP) and Computer Vision applications. Conduct research on cutting-edge techniques and tools in machine learning, NLP, and Computer Vision.
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The Manufacturing Technology Instructor teaches courses at a Community College in subject areas such as applied computer use, mathematics, blueprint reading and set up, calibration, and operation of complex machine tools.
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You have experience in one or more of the following : - recommender systems, predictive modeling, reinforcement learning (e.g., multi-armed bandits), personalized search, computational optimization, natural language processing, deep learning, causal inference especially as applied to e-commerce/marketplaces/email marketing.
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machine learning applied mathematics hands on jobs Company: Inspyr Solutions in Anoka, Minnesota
FEATURED BLOG POSTS
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.
Recruitment strategies that are weird, but actually workÂ
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.Â