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We are seeking a machine learning engineer to work closely with our product and research teams to develop SOTA deep learning software. Proven experience as a machine learning engineer or similar role.
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Absorb machine learning literature, particularly in natural language processing, and quickly prototype new techniques by engaging with relevant research papers and textbooks. Currently enrolled in or a recent graduate of a PhD or Master degree program in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
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Roles and Responsibilities: Conducting cutting-edge research in the fields of artificial intelligence, machine learning, and robotics, specifically as they relate to autonomous vehicle technology.
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Currently pursuing a PhD degree in Computer Science, Computer Security, Machine Learning, or a related technical discipline. Research experience in computer and network security such as Threat Detection, Threat Hunting, Anomaly Detection using Machine Learning, or engineering experience in building systems for such purpose.
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We provide self service tools to enable data discovery, data processing, data mining and research, reporting, and machine learning/AI, all built using OCI services and industry standard open source distributed computing tools.
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Who You Are: You are a dynamic Computational Scientist who will work with other scientists to apply cutting-edge computation, Machine Learning/Deep Learning approaches to revolutionize our large molecule computational tools by contributing to accelerating and improving the process of design and engineering of novel biologics drug candidates.
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This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and data wrangling, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.
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Our scientists have significant expertise across a diverse set of disciplines in computational biology, bioinformatics, and machine learning, including multi-omic data analysis, functional genomics, systems biology and biomarker analysis.
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Show advanced knowledge of Machine Learning Algorithms/AI techniques including Deep Learning Techniques (RNN, CNN, GAN, etc) Demonstrate ability to work with a variety of Deep learning frameworks including TensorFlow, Keras, Caffe, CNTK, etc.
$104,000 - $150,000 a yearTemporaryRemoteExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Develop strategies, standards and best practices in the areas of machine learning, data visualization and data integration and lead adoption throughout Ignite. This person will develop a deep understanding of the analytical need and leverage knowledge of Equifax data assets, big data technologies, data engineering, keying and linking concepts, build attributes and statistical models using traditional and modern machine learning techniques.
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LLM, RAG, Data engineer, Python, Pyspark, Machine learning, Gen AI, AI/ML, Vector database, Databricks, Snowflake, Education: Bachelor’s degree in engineering, Computer Science or a related field; Master’s degree is a plus.
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Are you a passionate Machine Learning Engineer with a strong background in SageMaker, prompt engineering, and LLM (Large Language Model) model tuning? If you are an ambitious Machine Learning Engineer with a proven track record in SageMaker, prompt engineering, and LLM model tuning, we would love to hear from you.
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Machine Learning and Deep Learning (Some or all): Deep neural networks(CNN, RNN, LSTM), Supervised methods such as Tree based models (random forest, xgboost, Light GBM), K-NN, SVM as well as Unsupervised methods such as Clustering (Hierarchical, K-mean, K-medoids), Dimensionality reduction (PCA.
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Employees in this role use knowledge of machine learning, optimization, statistics, and applied mathematics along with abilities in software engineering with a focus on distributed computing and data storage infrastructure (e.g. “Big Data.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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machine learning jobs Title: engineer Company: Applied Materials
FEATURED BLOG POSTS
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.
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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).