AI Research Intern Position – Microsoft AI Research Team
The Microsoft’s Commerce AI Research team in Israel develop cutting edge machine / deep learning algorithms in the domains of computer vision, natural language processing, audio analytics, recommender systems and more. Our algorithms are implemented in a wide array of Microsoft products (Dynamics365, Xbox, Windows Store, and more) that serve millions of users around the globe. Our research is regularly patented and published in top-tier machine learning and data mining conferences. The position offers a unique opportunity to join one of the best AI research teams in the country.
The Analytics organization at Earnix is charged with developing state of the art analytical and AI/ML solutions & algorithms that are embedded into Earnix suite of products. We are looking for an experienced, innovative & business savvy Analytics leader to join us and help us seek the next big analytical thing.
About the company:
Brodmann17 is developing game-changing Deep Learning and Computer Vision algorithms for ADAS and Automated Driving. We’re pioneering state of the art software products that achieve the best performance and accuracy, making it an ideal solution for the most demanding challenges of the fast growing automotive market. Come and join us in one of the most interesting AI companies, contributing to a life-saving product!
About the job:
We are looking for a Deep Learning engineer to join the Brodmann17 Chief Scientist’s team. In this position, you will build best in class infrastructure and tools for developing deep learning based ADAS and Autonomous Driving products. You’ll be a key member of designing, implementing and extending this platform that enables fast, continuous and flexible Deep Learning algorithms development. You will work closely with excellent researchers to understand the needs and requirements of the research as well as keep up to date with latest developments in the field.
Artbrain is a revolutionary company in the art and collectibles ecosystem.
We are transforming the art and collectibles market by creating a technology that matches collectors with the items they love. AKA a recommendation engine tailored for this amazing domain. But this is only the tip of the iceberg, and we are now working on our next suite of solutions.
We are looking for a Head of Machine Learning with great CS skills to lead our ML development. You should be an enthusiastic ML developer that lives & breathes ML while not being held back by your software skills. Our Machine Learning stack consists of all of the various algorithmic domains, from NLP to Reinforcement Learning. We want to emphasize that our perfect candidate should be able to “fly solo” by leading projects from end to end.
What we can offer a Head of Machine Learning
A top-notch data-driven company. Our Data Science group consists of ~50 people, of which there are 20+ data scientists and others (engineering, curation, and labeling) that help us make our projects successful and impactful for Wix. We apply SOTA Machine Learning techniques to Wix’s data to improve the product, internal processes, and personalisation for users, which in turn improves our profitability.
We’re looking for a Data Science team leader who’s passionate about data science, and specifically with time-series projects, to lead our Forecasting team.
We are looking for an extremely talented Data Scientist with at least 5 years of experience in data science, machine learning, and/or deep learning. You have a deep understanding of classical ML & DL algos for a wide spectrum of problems and domains and are familiar with time-series projects
You have the technical know-how to advise team members, the managerial skills to prioritize and advance projects, and the interpersonal skills to communicate data science to non-technical management. You also have a practical machine learning experience with Python. You’re willing to work hands-on, potentially working on your own projects while managing the team.
You have profound business acumen and are able to communicate model’s internals and externals to management, while also incorporating external feedback into the models.
Loora is reinventing the way we learn languages, making it possible for anyone to have their own personal fun and engaging AI English tutor.
Our innovative and unique consumer experience relies heavily on the state-of-the-art in domains such as text generation, dialog, question answering, grammar correction and knowledge-grounded LMs.
We are looking for an applied Deep Learning Researcher to join our growing core team. You will lead projects from research to production, solving real-world problems while pushing the limits of conversational AI. Join us now to truly impact the product we're building!
Even better if you have:
The Foundations of Deep Learning Lab at Tel Aviv University's School of Computer Science is looking for excellent research students to help develop a mathematical theory behind deep learning.
Deep learning is experiencing unprecedented success in recent years, delivering state of the art performance in a multitude of application domains. However, despite its extreme popularity and the vast attention it is receiving, our formal understanding of deep learning is limited. Its application in practice is based primarily on conventional wisdom, trial-and-error, and intuition, often leading to suboptimal results (compromising not only effectiveness, but also safety, privacy and/or fairness).
The Foundations of Deep Learning Lab at Tel Aviv University's School of Computer Science is developing a mathematical theory behind deep learning, with the aim of shedding light on existing empirical findings, and more importantly, leading to principled methods that bring forth improved performance and new capabilities. The lab is headed by Dr. Nadav Cohen, and regularly publishes in top tier machine learning venues (e.g. NeurIPS, ICML, ICLR). Its research is highly mathematical, but also includes extensive empirical evaluations that support theory. For more information please visit: https://www.cohennadav.com/.
We are looking for:
You, an excellent mathematically inclined research student, to join us, and help crack open the black box of deep learning. Typical entry to the lab is at MSc level, with the option of pursuing a subsequent PhD if there is mutual interest. Entry at PhD level is also possible, but only in exceptional cases. If interested in applying, please verify that you meet the criteria below, and if so, include in your application CV and grade transcripts.
Prospective MSc students:
* BSc from a well-known university, with GPA of at least 95.0/100 (or equivalent), in one of the following disciplines: (i) Mathematics; (ii) Mathematics & Computer Science; (iii) Mathematics & Electrical Engineering; or (iv) Mathematics & Physics.
* Successful completion of introductory course in machine learning (Tel Aviv University's course #0368323501 or equivalent)
* Solid Python programming skills
* Willingness and ability to devote full-time to research
* High degree of independence, work ethic and creativity
* Experience with deep learning frameworks (e.g. PyTorch or TensorFlow)
* Professional (industry) experience in machine learning
Prospective PhD students:
In addition to the requirements above, applicants interested in joining at PhD level are expected to meet at least one of the following:
* Proven track record in machine learning research (with publication in top-tier venues)
* Advanced coursework and research in either of the following: Statistics, Optimization, Dynamical Systems, Numerical Analysis, Quantum Physics or Quantum Computing.
At Quris Technologies Ltd. (TLV) we are developing the most advanced technology that will shape the future of drug discovery and clinical trials success prediction. In short, given a drug, we collect data from human cells and use it to predict clinical trial success. This is an opportunity to work closely with the top biologists at the edge of today's bio-tech.
We are seeking a sharp lead data scientist that will help us gain valuable insights from our proprietary data and shape with us the future of drug discovery and clinical trials success prediction.
You should have a strong statistical analysis capability as well as a solid understanding in Machine learning and Deep Learning.
This is a magnificent chance to join a leading technological company from an early stage and make a true impact.
Helping retailers and consumers interact is what we do – and what we’ve done for 130 years. NCR’s portfolio of retail solutions enables seamless consumer interactions, whether in the store, on the go or at home. Our innovative solutions address retailer needs in multiple industries from grocery to general merchandise to convenience stores and specialty retail including POS software, hardware, kiosks, digital signage, self-checkout, services and more.
What are we looking for?
We are looking for an experienced Senior Data Scientist to join our fresh R&D team. If data and statistics are your breakfast, algorithms are your dinner, and you’re passionate about solving complicated real-world challenges, deliver impact, and investigating human phenomena – please reach out!
Nice to have
Riskified empowers merchants and shoppers to realize the full potential of eCommerce by making it safe, accessible, and frictionless. Our global team helps the world’s most-innovative eCommerce merchants eliminate risk and uncertainty from their business. Merchants integrate Riskified’s machine learning platform to create trusted customer relationships, driving higher sales while reducing costs. Riskified has reviewed hundreds of millions of transactions and approved billions of dollars of revenue for global brands and fast-growing businesses across industries, including Wayfair, Wish, Peloton, Gucci, and many more. As of July 29th, 2021, Riskified has begun trading on NYSE under the ticker RSKD.
The Data Sources team is responsible for exploring and leveraging the various data sources that make Riskified’s models and products possible. The team proactively explores data sources that can contribute new information and value to our models, feature engineer the raw data, and evaluates the expected value from these sources by augmenting our production models and testing for performance lift. These data sources include 3rd party vendors, open source data, our internally developed beacon and any additional information that may be provided by our customers.
The team's data scientists are experts at exploratory analysis, can quickly dig into new noisy unstructured big data that has barely been touched before, and creatively manipulate it for model improvements.